Google Gemini 3.5 Transcribe is the synchronous model for converting complete, prerecorded audio files into written speech. It is based on Gemini’s audio-understanding capabilities, but has a transcription-specific input and output contract. The separate Gemini 3.5 Transcribe Live edition receives an audio stream and returns incremental results. This recorded-audio model produces a completed transcript, with optional word timing or speaker attribution depending on the selected configuration.
Prepare a clear recording with speech that is not severely clipped and with meaningful separation between voices where possible. The manufacturer’s synchronous examples pass WAV audio as file bytes or a stored audio resource, with its MIME type specified. Keep the original audio available for review. The intended result might be a checked interview transcript, a caption-alignment record or readable dictation; decide which artifact is needed before combining features that change the wording or add metadata.
Google documents language auto-detection across more than 85 languages, including code-mixing within a session. Language support levels vary, and a known language hint can improve recognition. Custom vocabulary supplies distinct names, brands or specialist terms that are likely to occur. The maker allows up to 1,000 terms and notes that focused lists of up to about 100 typically work best. Keep uncommon terms relevant to the recording and check them against the audio rather than assuming a vocabulary hint proves the term was spoken.
VERBATIM is the default mode. It preserves fillers, repetitions, false starts and spoken corrections so the text remains a record of the wording. This is the mode to use when the task needs word-level timestamps or speaker diarization. For an interview, for example, retain the original turns and timings, then correct important names and quantities by listening to the relevant passage. A later summary or polished article can use that checked record without silently replacing what the speaker said.
SMART mode is designed for readable dictation. It removes disfluencies, resolves inline self-corrections and structures spoken material into paragraphs or lists, with normalized dates and numbers where appropriate. A dictated task list can become a readable list rather than a string of spoken transitions. That processing changes the form of the transcript. Google explicitly states that SMART is incompatible with word timestamps and diarization, so choose it when readable text is the required artifact rather than attempting to use it as the timed, speaker-attributed record.
When word timing is enabled, the response includes recognized words with start and end offsets. These support locating a correction in the recording or preparing captions. The maker identifies an accuracy trade-off from enabling word-level timestamps. Review the text as well as the alignment, particularly around fast speech, overlap or unusual terminology. A useful timed transcript retains the word record and the source audio together instead of treating a fluent sentence as proof that its alignment is correct.
Speaker diarization identifies and labels voices in recorded audio, with up to eight speakers documented. Attribution for three or more speakers is described by the maker as experimental. Treat the labels as inferred speaker groupings and review transitions against the recording. A speaker label is not independent proof of a person’s identity or role. If the task needs names, associate the labels with known recording information rather than inventing identities from the recognized words.
The manufacturer’s feature table lists a 15-minute recorded-audio window, with file processing limited to that duration when features such as timestamps or diarization are enabled. Prepare longer source material as suitable segments while preserving their order and original time position. The model’s transcript, timed words and speaker-labeled parts are different result representations; retain the representation needed for the task. These audio-specific limits should not be replaced with context or duration figures from a general Gemini multimodal model. Google lists SMART formatting, word-level timestamps and speaker diarization as experimental features.
The output contract is transcription-specific. SMART formatting creates readable text but does not add a general JSON-schema response contract, tool-calling capability or an instruction-following assistant workflow. For the final artifact, check important wording, numbers and negations against the audio, preserve any unresolved segment for correction, and retain the selected mode with the result. This makes it clear whether the deliverable records the original spoken wording or presents an edited reading version derived from it.
", "aboutText": "Google Gemini 3.5 Transcribe is the synchronous model for converting complete, prerecorded audio files into written speech. It is based on Gemini’s audio-understanding capabilities, but has a transcription-specific input and output contract. The separate Gemini 3.5 Transcribe Live edition receives an audio stream and returns incremental results. This recorded-audio model produces a completed transcript, with optional word timing or speaker attribution depending on the selected configuration.\n\nPrepare a clear recording with speech that is not severely clipped and with meaningful separation between voices where possible. The manufacturer’s synchronous examples pass WAV audio as file bytes or a stored audio resource, with its MIME type specified. Keep the original audio available for review. The intended result might be a checked interview transcript, a caption-alignment record or readable dictation; decide which artifact is needed before combining features that change the wording or add metadata.\n\nGoogle documents language auto-detection across more than 85 languages, including code-mixing within a session. Language support levels vary, and a known language hint can improve recognition. Custom vocabulary supplies distinct names, brands or specialist terms that are likely to occur. The maker allows up to 1,000 terms and notes that focused lists of up to about 100 typically work best. Keep uncommon terms relevant to the recording and check them against the audio rather than assuming a vocabulary hint proves the term was spoken.\n\nVERBATIM is the default mode. It preserves fillers, repetitions, false starts and spoken corrections so the text remains a record of the wording. This is the mode to use when the task needs word-level timestamps or speaker diarization. For an interview, for example, retain the original turns and timings, then correct important names and quantities by listening to the relevant passage. A later summary or polished article can use that checked record without silently replacing what the speaker said.\n\nSMART mode is designed for readable dictation. It removes disfluencies, resolves inline self-corrections and structures spoken material into paragraphs or lists, with normalized dates and numbers where appropriate. A dictated task list can become a readable list rather than a string of spoken transitions. That processing changes the form of the transcript. Google explicitly states that SMART is incompatible with word timestamps and diarization, so choose it when readable text is the required artifact rather than attempting to use it as the timed, speaker-attributed record.\n\nWhen word timing is enabled, the response includes recognized words with start and end offsets. These support locating a correction in the recording or preparing captions. The maker identifies an accuracy trade-off from enabling word-level timestamps. Review the text as well as the alignment, particularly around fast speech, overlap or unusual terminology. A useful timed transcript retains the word record and the source audio together instead of treating a fluent sentence as proof that its alignment is correct.\n\nSpeaker diarization identifies and labels voices in recorded audio, with up to eight speakers documented. Attribution for three or more speakers is described by the maker as experimental. Treat the labels as inferred speaker groupings and review transitions against the recording. A speaker label is not independent proof of a person’s identity or role. If the task needs names, associate the labels with known recording information rather than inventing identities from the recognized words.\n\nThe manufacturer’s feature table lists a 15-minute recorded-audio window, with file processing limited to that duration when features such as timestamps or diarization are enabled. Prepare longer source material as suitable segments while preserving their order and original time position. The model’s transcript, timed words and speaker-labeled parts are different result representations; retain the representation needed for the task. These audio-specific limits should not be replaced with context or duration figures from a general Gemini multimodal model. Google lists SMART formatting, word-level timestamps and speaker diarization as experimental features.\n\nThe output contract is transcription-specific. SMART formatting creates readable text but does not add a general JSON-schema response contract, tool-calling capability or an instruction-following assistant workflow. For the final artifact, check important wording, numbers and negations against the audio, preserve any unresolved segment for correction, and retain the selected mode with the result. This makes it clear whether the deliverable records the original spoken wording or presents an edited reading version derived from it.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "eda010cbce1d2d606f35360dd487e0971acc52f55aa4c64c24d4cd5b194f7ff3", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "google/gemini-3.5-transcribeGoogle Gemini 3.5 Transcribe converts recorded speech to text with automatic language detection, custom vocabulary and optional word timing or speaker diarization. Choose VERBATIM for timing and speaker attribution, or SMART for readable dictation; SMART cannot be combined with those two features.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
Google Gemini 3.5 Transcribe is the synchronous model for converting complete, prerecorded audio files into written speech. It is based on Gemini’s audio-understanding capabilities, but has a transcription-specific input and output contract. The separate Gemini 3.5 Transcribe Live edition receives an audio stream and returns incremental results. This recorded-audio model produces a completed transcript, with optional word timing or speaker attribution depending on the selected configuration.
Prepare a clear recording with speech that is not severely clipped and with meaningful separation between voices where possible. The manufacturer’s synchronous examples pass WAV audio as file bytes or a stored audio resource, with its MIME type specified. Keep the original audio available for review. The intended result might be a checked interview transcript, a caption-alignment record or readable dictation; decide which artifact is needed before combining features that change the wording or add metadata.
Google documents language auto-detection across more than 85 languages, including code-mixing within a session. Language support levels vary, and a known language hint can improve recognition. Custom vocabulary supplies distinct names, brands or specialist terms that are likely to occur. The maker allows up to 1,000 terms and notes that focused lists of up to about 100 typically work best. Keep uncommon terms relevant to the recording and check them against the audio rather than assuming a vocabulary hint proves the term was spoken.
VERBATIM is the default mode. It preserves fillers, repetitions, false starts and spoken corrections so the text remains a record of the wording. This is the mode to use when the task needs word-level timestamps or speaker diarization. For an interview, for example, retain the original turns and timings, then correct important names and quantities by listening to the relevant passage. A later summary or polished article can use that checked record without silently replacing what the speaker said.
SMART mode is designed for readable dictation. It removes disfluencies, resolves inline self-corrections and structures spoken material into paragraphs or lists, with normalized dates and numbers where appropriate. A dictated task list can become a readable list rather than a string of spoken transitions. That processing changes the form of the transcript. Google explicitly states that SMART is incompatible with word timestamps and diarization, so choose it when readable text is the required artifact rather than attempting to use it as the timed, speaker-attributed record.
When word timing is enabled, the response includes recognized words with start and end offsets. These support locating a correction in the recording or preparing captions. The maker identifies an accuracy trade-off from enabling word-level timestamps. Review the text as well as the alignment, particularly around fast speech, overlap or unusual terminology. A useful timed transcript retains the word record and the source audio together instead of treating a fluent sentence as proof that its alignment is correct.
Speaker diarization identifies and labels voices in recorded audio, with up to eight speakers documented. Attribution for three or more speakers is described by the maker as experimental. Treat the labels as inferred speaker groupings and review transitions against the recording. A speaker label is not independent proof of a person’s identity or role. If the task needs names, associate the labels with known recording information rather than inventing identities from the recognized words.
The manufacturer’s feature table lists a 15-minute recorded-audio window, with file processing limited to that duration when features such as timestamps or diarization are enabled. Prepare longer source material as suitable segments while preserving their order and original time position. The model’s transcript, timed words and speaker-labeled parts are different result representations; retain the representation needed for the task. These audio-specific limits should not be replaced with context or duration figures from a general Gemini multimodal model. Google lists SMART formatting, word-level timestamps and speaker diarization as experimental features.
The output contract is transcription-specific. SMART formatting creates readable text but does not add a general JSON-schema response contract, tool-calling capability or an instruction-following assistant workflow. For the final artifact, check important wording, numbers and negations against the audio, preserve any unresolved segment for correction, and retain the selected mode with the result. This makes it clear whether the deliverable records the original spoken wording or presents an edited reading version derived from it.
POST /v1/audio/transcriptionsaudiotext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits google/gemini-3.5-transcribe | Default— |
Fieldinput_audio | Typeobject | RequirementRequired | Values & limits | Default— |
Fieldlanguage | Typestring | RequirementOptional | Values & limits | Default— |
Fieldtemperature | Typenumber | RequirementOptional | Values & limits Minimum: 0 Maximum: 1 | Default— |
Fieldresponse_format | Typestring | RequirementOptional | Values & limits json, verbose_json | Defaultjson |
Fieldtimestamp_granularities | Typearray | RequirementOptional | Values & limits | Default— |
Fieldprovider | Typeobject | RequirementOptional | Values & limits | Default— |
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, input_audio |
Parametermaterial_types | Contractaudio |
Parametermaterial_conditions | ContractRead an actual WAV file and encode its real bytes for the declared JSON input_audio; no multipart route is advertised for this exact JSON-only declaration. |
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}
The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.
Tariff references do not add request options. Supported parameters are listed for the selected method.
Match each charge to the conditions shown. Use one rate for each set of alternative configurations.
| Configuration | Rate schedule | Forecast quantity | Billing unit | Charge |
|---|---|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Forecast quantity— | Billing unit— | Charge Input · Input tokens · Estimate for comparison only — / 1K tokens Output · Output tokens · Estimate for comparison only — / 1K tokens Input · Cache read · Estimate for comparison only — / 1K tokens Input · Cache write · Estimate for comparison only — / 1K tokens Input · Cache write, 1 hour · Estimate for comparison only — / 1K tokens |
| Configurationinput token | Rate schedule— | Forecast quantity— | Billing unit/ 1K tokens | Charge Input · input token · Estimate for comparison only $0.004 / 1K tokens |
| Configurationoutput token | Rate schedule— | Forecast quantity— | Billing unit/ 1K tokens | Charge Output · output token · Estimate for comparison only $0.024 / 1K tokens |
| ConfigurationEstimated generation cost | Rate schedule— | Forecast quantityone generation estimate | Billing unit— | Charge Output · Estimated generation cost · Estimate for comparison only $1.179648 estimate before generation This estimate is not an additional charge or a fixed rate for the completed generation. |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_AUDIO_FILE:?Set the path to your actual WAV recording}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nimport base64\naudio=Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4]==b'RIFF' and audio[8:12]==b'WAVE'): raise SystemExit('Supply an actual WAV audio file')\nif len(audio)>26214400: raise SystemExit('Use a documented supported large-file flow')\nrequest={'model': 'google/gemini-3.5-transcribe', 'input_audio': {'data': '${BASE64_ACTUAL_WAV_BYTES}', 'format': 'wav'}}\nrequest['input_audio']['data']=base64.b64encode(audio).decode('ascii')\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o response.bin\n# Keep the complete original response and headers. Read every returned segment, word and usage field.\n# Preserve actual operation/task/asset IDs; continue reads of the original result without resubmitting.\nGET /v1/media/tasks/{task_id}GET /v1/media/assets/{asset_id}/contentGET /v1/media/assetsGET /v1/media/assets/{asset_id}set -eu\n: "${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 owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\nKeep every complete returned response, file and content part.
Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.
Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation.
| Field | Type |
|---|---|
Fieldtext | Type |
Fieldusage | Type |
Fieldsegments[] | Type |
Fieldwords[] | Type |
Fieldspeaker fields | Type |
Fieldtimestamps | Type |
Ailoot Ultra google/gemini-3.5-transcribe
Use the method paths shown above.