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Whisper 1 is OpenAI’s general-purpose speech-recognition API model, documented as powered by the open-source Whisper V2 model. It accepts an audio file and returns text. The maker describes multilingual recognition, language identification and a separate speech-translation task. Transcription preserves the spoken language; the producer’s separate translation interface returns English text.

A useful application is preparing an interview, voice note or recorded conversation for later search and editing. Supply the completed recording and, when known, its input language. OpenAI documents 98 supported languages and notes that recognition accuracy varies by language. The singular language hint uses an ISO 639-1 code; the newer multi-language and keyword fields of other transcription models are separate controls.

The producer’s file-transcription flow accepts files up to 25 MB in MP3, MP4, MPEG, MPGA, M4A, WAV or WebM format. For a larger recording, use a compressed format or divide it into chunks within the limit. Preserve sentence boundaries and the order of the chunks so that the assembled transcript remains connected to the original recording. A video container supplies its audio for this task rather than a visual-description input.

A prompt can supply names, acronyms or recording-specific vocabulary and context from an earlier segment. Whisper’s prompt limit is 224 tokens, and the prompt should match the audio’s language. The maker states that Whisper does not follow instructions like a general-purpose text model. Use the prompt as relevant transcription context, then check important spellings against the recording rather than treating a terminology list as words the speaker must have said.

The producer documents JSON, plain text, SRT, VTT and verbose JSON transcription formats. Word and segment timestamps require verbose JSON; either or both granularities can be requested. The API reference notes that segment timestamps add no extra latency, while word timestamps require additional processing. These outputs support captioning and locating passages during editing; speaker-diarization annotations belong to a different specialized model.

Whisper 1 does not support file-transcription streaming. Its reference also documents a sampling temperature between zero and one; at zero, the model can increase temperature automatically when its decoding thresholds require it. This describes the producer’s processing controls rather than a promise that every recording produces an identical or perfectly accurate transcript.

Define the final artifact: a transcript for search, a subtitle file or text with word/segment timing. Keep the original recording, chunk order and relevant source time references with the result. A later text-editing step can correct a misspelling or prepare a summary, but compare changes with the audio so the speaker’s meaning is preserved. The recognized text becomes evidence for the next task rather than a generated answer to the spoken question.

", "aboutText": "Whisper 1 is OpenAI’s general-purpose speech-recognition API model, documented as powered by the open-source Whisper V2 model. It accepts an audio file and returns text. The maker describes multilingual recognition, language identification and a separate speech-translation task. Transcription preserves the spoken language; the producer’s separate translation interface returns English text.\n\nA useful application is preparing an interview, voice note or recorded conversation for later search and editing. Supply the completed recording and, when known, its input language. OpenAI documents 98 supported languages and notes that recognition accuracy varies by language. The singular language hint uses an ISO 639-1 code; the newer multi-language and keyword fields of other transcription models are separate controls.\n\nThe producer’s file-transcription flow accepts files up to 25 MB in MP3, MP4, MPEG, MPGA, M4A, WAV or WebM format. For a larger recording, use a compressed format or divide it into chunks within the limit. Preserve sentence boundaries and the order of the chunks so that the assembled transcript remains connected to the original recording. A video container supplies its audio for this task rather than a visual-description input.\n\nA prompt can supply names, acronyms or recording-specific vocabulary and context from an earlier segment. Whisper’s prompt limit is 224 tokens, and the prompt should match the audio’s language. The maker states that Whisper does not follow instructions like a general-purpose text model. Use the prompt as relevant transcription context, then check important spellings against the recording rather than treating a terminology list as words the speaker must have said.\n\nThe producer documents JSON, plain text, SRT, VTT and verbose JSON transcription formats. Word and segment timestamps require verbose JSON; either or both granularities can be requested. The API reference notes that segment timestamps add no extra latency, while word timestamps require additional processing. These outputs support captioning and locating passages during editing; speaker-diarization annotations belong to a different specialized model.\n\nWhisper 1 does not support file-transcription streaming. Its reference also documents a sampling temperature between zero and one; at zero, the model can increase temperature automatically when its decoding thresholds require it. This describes the producer’s processing controls rather than a promise that every recording produces an identical or perfectly accurate transcript.\n\nDefine the final artifact: a transcript for search, a subtitle file or text with word/segment timing. Keep the original recording, chunk order and relevant source time references with the result. A later text-editing step can correct a misspelling or prepare a summary, but compare changes with the audio so the speaker’s meaning is preserved. The recognized text becomes evidence for the next task rather than a generated answer to the spoken question.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "53ee00705588fc7a53964f51cb522bc17cbf6fb5af16615767c27d30832f75d7", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "
O

OpenAI: Whisper 1

OpenAI /openai/whisper-1

Overview

Whisper 1 transcribes a completed audio file into text, with multilingual recognition and word or segment timestamps. The producer supports subtitle formats and a separate English-translation flow; the transcription result preserves the recording’s language.

Accepted inputs
Audio
Results
transcription
About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Whisper 1 is OpenAI’s general-purpose speech-recognition API model, documented as powered by the open-source Whisper V2 model. It accepts an audio file and returns text. The maker describes multilingual recognition, language identification and a separate speech-translation task. Transcription preserves the spoken language; the producer’s separate translation interface returns English text.

A useful application is preparing an interview, voice note or recorded conversation for later search and editing. Supply the completed recording and, when known, its input language. OpenAI documents 98 supported languages and notes that recognition accuracy varies by language. The singular language hint uses an ISO 639-1 code; the newer multi-language and keyword fields of other transcription models are separate controls.

The producer’s file-transcription flow accepts files up to 25 MB in MP3, MP4, MPEG, MPGA, M4A, WAV or WebM format. For a larger recording, use a compressed format or divide it into chunks within the limit. Preserve sentence boundaries and the order of the chunks so that the assembled transcript remains connected to the original recording. A video container supplies its audio for this task rather than a visual-description input.

A prompt can supply names, acronyms or recording-specific vocabulary and context from an earlier segment. Whisper’s prompt limit is 224 tokens, and the prompt should match the audio’s language. The maker states that Whisper does not follow instructions like a general-purpose text model. Use the prompt as relevant transcription context, then check important spellings against the recording rather than treating a terminology list as words the speaker must have said.

The producer documents JSON, plain text, SRT, VTT and verbose JSON transcription formats. Word and segment timestamps require verbose JSON; either or both granularities can be requested. The API reference notes that segment timestamps add no extra latency, while word timestamps require additional processing. These outputs support captioning and locating passages during editing; speaker-diarization annotations belong to a different specialized model.

Whisper 1 does not support file-transcription streaming. Its reference also documents a sampling temperature between zero and one; at zero, the model can increase temperature automatically when its decoding thresholds require it. This describes the producer’s processing controls rather than a promise that every recording produces an identical or perfectly accurate transcript.

Define the final artifact: a transcript for search, a subtitle file or text with word/segment timing. Keep the original recording, chunk order and relevant source time references with the result. A later text-editing step can correct a misspelling or prepare a summary, but compare changes with the audio so the speaker’s meaning is preserved. The recognized text becomes evidence for the next task rather than a generated answer to the spoken question.

Available in Ailoot · inputs & methods

Ailoot Ultra · Speech recognition POST /v1/audio/transcriptions
Input types
audio
Output types
transcription
Output format
json
FieldTypeRequirementValues & limitsDefault
FieldmodelTypestringRequirementRequiredValues & limits
openai/whisper-1
Default—
FieldfileTypefileRequirementRequiredValues & limits
Content type: multipart/form-data
Default—
Fieldresponse_formatTypestringRequirementOptionalValues & limits
json
Default—
Fieldinput_audio.dataTypebase64_stringRequirementRequiredValues & limits
Applies when: WhisperOR JSON input
Default—
Fieldinput_audio.formatTypestringRequirementRequiredValues & limits
wav, mp3, flac, ogg, m4a, webm
Applies when: WhisperOR JSON input
Default—
Input material combinations

· Required: model, file

Method parameters and lifecycle
ParameterContract
ParametercontoursContract{"content_types":["application/json","multipart/form-data"],"required_json":["model","input_audio.data","input_audio.format"],"required_multipart":["model","file"],"file_formats":["wav","mp3","flac","ogg","m4a","webm"],"response_format_optional":["json"]}, {"content_types":["multipart/form-data"],"required":["model","file"],"file_formats":["mp3"],"response_format_option":false}
Parametermax_bytesContract26214400
Parametermaterial_typesContractaudio

Lifecycle: synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · actual returned task_id or media library record

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

Use actual recording and matching format.

Preserve full transcript, segments, speaker IDs and timing.

Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode
Not specified When fast mode is selected
Flex mode
Not specified When flex mode is selected
Maximum reasoning effort
Not specified When maximum reasoning effort uses the default adjustment

Ailoot rates

Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

ConfigurationRate scheduleBilling unitCharge
ConfigurationBase token ratesRate scheduleBase rateBilling unit—Charge
Input · Input tokens — / 1K tokens
Output · Output tokens — / 1K tokens
Input · Cache read — / 1K tokens
Input · Cache write — / 1K tokens
Input · Cache write, 1 hour — / 1K tokens
Configurationinput audio secondRate schedule—Billing unitper input audio secondCharge
Input · input audio second $0.0002 per input audio second

Reference tariff details

Model-level reference schedules do not change method selection, quotes or charges. Active charges use the selected Ailoot method rates.

OpenAI: Whisper 1

Prices by configuration

ConfigurationBilling conditionsCharge
ConfigurationOpenAI: Whisper 1 · Default configurationBilling conditionsDefault configurationCharge
Input · Input audio seconds $0.0002 per input audio second

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →

Example requests

Ailoot Ultra · Speech recognition

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_AUDIO_FILE:?Set the path to your actual MP3 recording}"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport os\nfrom pathlib import Path\np=Path(os.environ["AILOOT_AUDIO_FILE"])\nif not p.is_file() or p.suffix.lower()!=".mp3":raise SystemExit("Choose an existing MP3 recording")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" \\\n  --form-string model=openai/whisper-1 -F "file=@$AILOOT_AUDIO_FILE" \\\n  -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text())))\nPY_RESULT\n

Receive and save results

Ailoot Ultra · Speech recognition

json

Other content reads
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -o media-assets.json\n
Keep all completed results

Keep every complete returned response, file and content part.

Retain complete JSON, not only text; preserve every available segment/speaker/timestamp and actual task/asset identity.

If the original response needs checking

Retain original operation_id/X-Client-Request-ID for reconciliation without resubmission; no dedicated audio poll route.

Response fields
FieldType
FieldtextTypestring
Fieldsegments[]Typeobject
Fieldtask_idTypestring
Fieldasset_urlTypestring
FieldusageTypeobject
Errors and next steps
ResponseConditionNext step
Response400 · invalid_request_errorConditionInvalid required fields, material representation or parameter valueNext stepCorrect the indicated fields before a new creation request.
Responseserver_errorConditionThe returned response says the operation or result requires a checkNext stepKeep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request.

Aliases

Model aliases

Ailoot Ultra openai/whisper-1

Method path aliases

Use the method paths shown above.

Related caller IDs

openai/whisper-1

", "method_identity": { "effective_request_model_id": "openai/whisper-1", "fmt": "transcriptions", "http": "POST", "path": "/v1/audio/transcriptions", "request_model_id": "openai/whisper-1", "route_label": "Ultra" }, "method_key": "Ultra|transcriptions|/v1/audio/transcriptions|openai%2Fwhisper-1", "ordinal": 0, "rawMethod": { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain complete JSON, not only text; preserve every available segment/speaker/timestamp and actual task/asset identity.", "errors": [ { "code": null, "condition": "Invalid required fields, material representation or parameter value", "http_status": 400, "recovery": "Correct the indicated fields before a new creation request.", "type": "invalid_request_error" }, { "code": null, "condition": "The returned response says the operation or result requires a check", "http_status": null, "recovery": "Keep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request.", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "Retain original operation_id/X-Client-Request-ID for reconciliation without resubmission; no dedicated audio poll route." }, "limits": { "decoded_audio_max_bytes": 26214400 }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_formats": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "required_json": [ "model", "input_audio.data", "input_audio.format" ], "required_multipart": [ "model", "file" ], "response_format_optional": [ "json" ] }, { "content_types": [ "multipart/form-data" ], "file_formats": [ "mp3" ], "required": [ "model", "file" ], "response_format_option": false } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "speech_to_text" ], "outputs": { "all_results": "Retain complete JSON, not only text; preserve every available segment/speaker/timestamp and actual task/asset identity.", "family": "transcription", "fields": [ { "description": null, "name": "text", "type": "string" }, { "description": null, "name": "segments[]", "type": "object" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "asset_url", "type": "string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "openai/whisper-1" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "content_type": "multipart/form-data", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "file", "required": true, "type": "file" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_audio.data", "required": true, "type": "base64_string", "when": "WhisperOR JSON input" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "enum_known": true, "name": "input_audio.format", "required": true, "type": "string", "when": "WhisperOR JSON input" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "unlistedtranscriptionoptions", "formatlabelthatdiffersfromactualbytes" ] }, "hints": [ "Use actual recording and matching format.", "Preserve full transcript, segments, speaker IDs and timing." ], "input": { "contours": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_formats": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "required_json": [ "model", "input_audio.data", "input_audio.format" ], "required_multipart": [ "model", "file" ], "response_format_optional": [ "json" ] }, { "content_types": [ "multipart/form-data" ], "file_formats": [ "mp3" ], "required": [ "model", "file" ], "response_format_option": false } ], "material_types": [ "audio" ], "max_bytes": 26214400 }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "Retain original operation_id/X-Client-Request-ID for reconciliation without resubmission; no dedicated audio poll route." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/audio/transcriptions" }, "method_aliases": [], "operation_modes": [ "speech_to_text" ], "output": { "family": "transcription", "format": "json", "http_success": 200, "owned_result_fields_302": [ "task_id", "asset_url" ], "result": "owned complete JSON transcript" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "quoted_unit": "per input audio second" }, "label": "input audio second", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } ], "declared_tariff_references": [ { "client_selectable": false, "key": "9f485f9d704ef2cd14f1", "label": "OpenAI: Whisper 1", "profiles": [ { "basis": "", "dimensions": { "conditions": "Default configuration" }, "label": "OpenAI: Whisper 1 · Default configuration", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_physical_unit", "billing_input": false, "key": "d4e53ea51572a9d8f9fcc8e4", "label": "Input audio seconds", "public_unit_label": "per input audio second", "quantity": "1", "rate_role": "declared_tariff_rate", "side": "in", "unit": "input_audio_second" } ] } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual MP3 recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport os\nfrom pathlib import Path\np=Path(os.environ[\"AILOOT_AUDIO_FILE\"])\nif not p.is_file() or p.suffix.lower()!=\".mp3\":raise SystemExit(\"Choose an existing MP3 recording\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" \\\n --form-string model=openai/whisper-1 -F \"file=@$AILOOT_AUDIO_FILE\" \\\n -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text())))\nPY_RESULT\n", "label": "curl", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-assets.json\n", "label": "List actual media assets", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_MEDIA_TASK_ID:?Set the actual ID returned by the response or media-library metadata}\"\nexport AILOOT_MEDIA_TASK_ID\nresource_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ[\"AILOOT_MEDIA_TASK_ID\"],safe=\"\"))')\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/media/tasks/$resource_id\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-task.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"media-task.json\").read_text())))\nPY_RESULT\n", "label": "Read actual media task", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_ASSET_ID:?Set the actual ID returned by the response or media-library metadata}\"\nexport AILOOT_ASSET_ID\nresource_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ[\"AILOOT_ASSET_ID\"],safe=\"\"))')\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/media/assets/$resource_id\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-asset.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"media-asset.json\").read_text())))\nPY_RESULT\n", "label": "Read actual asset metadata", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "transcriptions", "hints": [ "Use actual recording and matching format.", "Preserve full transcript, segments, speaker IDs and timing." ], "http": "POST", "in": null, "input": [ "audio" ], "label": "Распознавание речи", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": null, "output": [ "transcription" ], "path": "/v1/audio/transcriptions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "per_request", "image_input_price": null, "image_output_price": null, "per_request_price": null, "unit_prices": { "audio_input_second": 0.0002 } }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "quoted_unit": "per input audio second" }, "label": "input audio second", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } ], "request_model_id": "openai/whisper-1", "route_label": "Ultra", "status_reads": [ "GET /v1/media/tasks/{task_id}", "GET /v1/media/assets/{asset_id}/content" ], "tiers": [], "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } } ], "model_id": "openai/whisper-1", "nativeProvenance": { "input_facts_canonical_sha256": "df3431ae9d02fd87c0d213d5c960ba50e737e4add086df0c563a90219bdd5c31", "input_html_sha256": "7a06e3992865da404411428438833b15e351ac708974ff9019edff3535aa9539", "private_audit_sha256": "921a4105096e172f98f3b25805c8bcb58ef09f7c40f677fc04b47d9e7f0ffe7b", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/en/openai-whisper-1/", "description": "Whisper 1 transcribes a completed audio file into text, with multilingual recognition and word or segment timestamps. The producer supports subtitle formats and a separate English-translation flow; the transcription result preserves the recording’s language.", "locale": "en", "md_url": "https://ailoot.ai/models/en/openai-whisper-1/index.md", "title": "OpenAI: Whisper 1 — Ailoot", "url": "https://ailoot.ai/models/en/openai-whisper-1/" }, "rawModel": { "about": "Whisper 1 is OpenAI’s general-purpose speech-recognition API model, documented as powered by the open-source Whisper V2 model. It accepts an audio file and returns text. The maker describes multilingual recognition, language identification and a separate speech-translation task. Transcription preserves the spoken language; the producer’s separate translation interface returns English text.\n\nA useful application is preparing an interview, voice note or recorded conversation for later search and editing. Supply the completed recording and, when known, its input language. OpenAI documents 98 supported languages and notes that recognition accuracy varies by language. The singular language hint uses an ISO 639-1 code; the newer multi-language and keyword fields of other transcription models are separate controls.\n\nThe producer’s file-transcription flow accepts files up to 25 MB in MP3, MP4, MPEG, MPGA, M4A, WAV or WebM format. For a larger recording, use a compressed format or divide it into chunks within the limit. Preserve sentence boundaries and the order of the chunks so that the assembled transcript remains connected to the original recording. A video container supplies its audio for this task rather than a visual-description input.\n\nA prompt can supply names, acronyms or recording-specific vocabulary and context from an earlier segment. Whisper’s prompt limit is 224 tokens, and the prompt should match the audio’s language. The maker states that Whisper does not follow instructions like a general-purpose text model. Use the prompt as relevant transcription context, then check important spellings against the recording rather than treating a terminology list as words the speaker must have said.\n\nThe producer documents JSON, plain text, SRT, VTT and verbose JSON transcription formats. Word and segment timestamps require verbose JSON; either or both granularities can be requested. The API reference notes that segment timestamps add no extra latency, while word timestamps require additional processing. These outputs support captioning and locating passages during editing; speaker-diarization annotations belong to a different specialized model.\n\nWhisper 1 does not support file-transcription streaming. Its reference also documents a sampling temperature between zero and one; at zero, the model can increase temperature automatically when its decoding thresholds require it. This describes the producer’s processing controls rather than a promise that every recording produces an identical or perfectly accurate transcript.\n\nDefine the final artifact: a transcript for search, a subtitle file or text with word/segment timing. Keep the original recording, chunk order and relevant source time references with the result. A later text-editing step can correct a misspelling or prepare a summary, but compare changes with the audio so the speaker’s meaning is preserved. The recognized text becomes evidence for the next task rather than a generated answer to the spoken question.", "alias_of": null, "aliases": [], "author": "OpenAI", "available": null, "canonical_model": "openai/whisper-1", "capabilities": { "context_length": 0, "manufacturer_input": [ "audio" ], "manufacturer_output": [ "transcription" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ], "summary": "Full configuration pricing in details." } ], "ctx": null, "entity_type": "model", "formats": [ "transcriptions" ], "id": "openai/whisper-1", "input": [ "audio" ], "kind": "transcription", "max_out": null, "methods": [ { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain complete JSON, not only text; preserve every available segment/speaker/timestamp and actual task/asset identity.", "errors": [ { "code": null, "condition": "Invalid required fields, material representation or parameter value", "http_status": 400, "recovery": "Correct the indicated fields before a new creation request.", "type": "invalid_request_error" }, { "code": null, "condition": "The returned response says the operation or result requires a check", "http_status": null, "recovery": "Keep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request.", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "Retain original operation_id/X-Client-Request-ID for reconciliation without resubmission; no dedicated audio poll route." }, "limits": { "decoded_audio_max_bytes": 26214400 }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_formats": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "required_json": [ "model", "input_audio.data", "input_audio.format" ], "required_multipart": [ "model", "file" ], "response_format_optional": [ "json" ] }, { "content_types": [ "multipart/form-data" ], "file_formats": [ "mp3" ], "required": [ "model", "file" ], "response_format_option": false } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "speech_to_text" ], "outputs": { "all_results": "Retain complete JSON, not only text; preserve every available segment/speaker/timestamp and actual task/asset identity.", "family": "transcription", "fields": [ { "description": null, "name": "text", "type": "string" }, { "description": null, "name": "segments[]", "type": "object" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "asset_url", "type": "string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "openai/whisper-1" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "content_type": "multipart/form-data", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "file", "required": true, "type": "file" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_audio.data", "required": true, "type": "base64_string", "when": "WhisperOR JSON input" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "enum_known": true, "name": "input_audio.format", "required": true, "type": "string", "when": "WhisperOR JSON input" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "unlistedtranscriptionoptions", "formatlabelthatdiffersfromactualbytes" ] }, "hints": [ "Use actual recording and matching format.", "Preserve full transcript, segments, speaker IDs and timing." ], "input": { "contours": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_formats": [ "wav", "mp3", "flac", "ogg", "m4a", "webm" ], "required_json": [ "model", "input_audio.data", "input_audio.format" ], "required_multipart": [ "model", "file" ], "response_format_optional": [ "json" ] }, { "content_types": [ "multipart/form-data" ], "file_formats": [ "mp3" ], "required": [ "model", "file" ], "response_format_option": false } ], "material_types": [ "audio" ], "max_bytes": 26214400 }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "Retain original operation_id/X-Client-Request-ID for reconciliation without resubmission; no dedicated audio poll route." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/audio/transcriptions" }, "method_aliases": [], "operation_modes": [ "speech_to_text" ], "output": { "family": "transcription", "format": "json", "http_success": 200, "owned_result_fields_302": [ "task_id", "asset_url" ], "result": "owned complete JSON transcript" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "quoted_unit": "per input audio second" }, "label": "input audio second", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } ], "declared_tariff_references": [ { "client_selectable": false, "key": "9f485f9d704ef2cd14f1", "label": "OpenAI: Whisper 1", "profiles": [ { "basis": "", "dimensions": { "conditions": "Default configuration" }, "label": "OpenAI: Whisper 1 · Default configuration", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_physical_unit", "billing_input": false, "key": "d4e53ea51572a9d8f9fcc8e4", "label": "Input audio seconds", "public_unit_label": "per input audio second", "quantity": "1", "rate_role": "declared_tariff_rate", "side": "in", "unit": "input_audio_second" } ] } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual MP3 recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport os\nfrom pathlib import Path\np=Path(os.environ[\"AILOOT_AUDIO_FILE\"])\nif not p.is_file() or p.suffix.lower()!=\".mp3\":raise SystemExit(\"Choose an existing MP3 recording\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" \\\n --form-string model=openai/whisper-1 -F \"file=@$AILOOT_AUDIO_FILE\" \\\n -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text())))\nPY_RESULT\n", "label": "curl", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-assets.json\n", "label": "List actual media assets", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_MEDIA_TASK_ID:?Set the actual ID returned by the response or media-library metadata}\"\nexport AILOOT_MEDIA_TASK_ID\nresource_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ[\"AILOOT_MEDIA_TASK_ID\"],safe=\"\"))')\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/media/tasks/$resource_id\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-task.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"media-task.json\").read_text())))\nPY_RESULT\n", "label": "Read actual media task", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_ASSET_ID:?Set the actual ID returned by the response or media-library metadata}\"\nexport AILOOT_ASSET_ID\nresource_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ[\"AILOOT_ASSET_ID\"],safe=\"\"))')\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/media/assets/$resource_id\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o media-asset.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"media-asset.json\").read_text())))\nPY_RESULT\n", "label": "Read actual asset metadata", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "transcriptions", "hints": [ "Use actual recording and matching format.", "Preserve full transcript, segments, speaker IDs and timing." ], "http": "POST", "in": null, "input": [ "audio" ], "label": "Распознавание речи", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": null, "output": [ "transcription" ], "path": "/v1/audio/transcriptions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "per_request", "image_input_price": null, "image_output_price": null, "per_request_price": null, "unit_prices": { "audio_input_second": 0.0002 } }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "quoted_unit": "per input audio second" }, "label": "input audio second", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } ], "request_model_id": "openai/whisper-1", "route_label": "Ultra", "status_reads": [ "GET /v1/media/tasks/{task_id}", "GET /v1/media/assets/{asset_id}/content" ], "tiers": [], "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.0002", "amount_unit": "usd_per_exact_native_unit", "billing_input": true, "estimate_only": false, "key": "audio_input_second", "label": "input audio second", "native_amount_usd_per_unit": "0.0002", "native_quantity": 1, "public_unit_label": "per input audio second", "quantity": 1, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "audio_input_second" } ] } ], "model_aliases": [ { "canonical_model_id": "openai/whisper-1", "request_model_id": "openai/whisper-1", "route_label": "Ultra" } ], "name": "OpenAI: Whisper 1", "price": { "in": null, "in_label": null, "out": null, "out_label": null, "sort_in": null, "sort_out": null, "varies": true }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Ultra", "units": [ { "amount": "0.0002", "amount_unit": "usd_per_declared_unit", "conditions": {}, "key": "prompt", "label": "prompt", "quantity": "1", "rate_role": "typed_active_maker_rate", "side": "in", "unit": "input_audio_second" } ] } ], "public_id": "openai/whisper-1", "short": "Whisper 1 transcribes a completed audio file into text, with multilingual recognition and word or segment timestamps. The producer supports subtitle formats and a separate English-translation flow; the transcription result preserves the recording’s language." }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "Whisper 1 transcribes a completed audio file into text, with multilingual recognition and word or segment timestamps. The producer supports subtitle formats and a separate English-translation flow; the transcription result preserves the recording’s language.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "608e8e27554be709d2b5abd67195bfb3872fb128a23541ba3095967cb7b60615", "renderer_sha256": "fed50305bd3bcc4980ac14df23640efb8c1bc1e819f9d53643d6f43e8974d3fe" }, "sourceRevision": "2155cde8476ddc22126d49c8381e4bb7917f8be642988aabbe8403b7fd58be25" }