GLM-4.1V-Thinking-Flash combines visual understanding with built-in reasoning. Zhipu describes the model for interpreting images and document pages, including charts, mathematical problems, interface structure and visual grounding. Its purpose is to connect what appears in the material with an explanation of the answer.
For a chart, preserve the axis labels, legend and units, then name the comparison or calculation. For a diagram, provide the problem statement and readable annotations. For an interface, identify the user’s goal and the controls or layout to examine. These details help distinguish a visible observation from an assumption.
Request a chart interpretation, a worked solution, a description of the relevant interface elements or a frontend implementation brief. Keep the source image with the answer, and check the labels, quantities and locations that the result depends on.
Through Ailoot, use the exact model ID in /v1/chat/completions and keep the image with its question in the conversation. The image content form uses image_url; supported image sources can carry an image address or base64 data URI. Collect the full JSON answer or all SSE segments when stream is enabled, and retain usage with the completed result.
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This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
GLM-4.1V-Thinking-Flash combines visual understanding with built-in reasoning. Zhipu describes the model for interpreting images and document pages, including charts, mathematical problems, interface structure and visual grounding. Its purpose is to connect what appears in the material with an explanation of the answer.
For a chart, preserve the axis labels, legend and units, then name the comparison or calculation. For a diagram, provide the problem statement and readable annotations. For an interface, identify the user’s goal and the controls or layout to examine. These details help distinguish a visible observation from an assumption.
Request a chart interpretation, a worked solution, a description of the relevant interface elements or a frontend implementation brief. Keep the source image with the answer, and check the labels, quantities and locations that the result depends on.
Through Ailoot, use the exact model ID in /v1/chat/completions and keep the image with its question in the conversation. The image content form uses image_url; supported image sources can carry an image address or base64 data URI. Collect the full JSON answer or all SSE segments when stream is enabled, and retain usage with the completed result.
POST /v1/chat/completionstext, imagetext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits glm-4.1v-thinking-flash Conditions: Use this exact Ailoot routing selector. | Default— |
Fieldmessages | Typearray | RequirementRequired | Values & limits Conditions: | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits Conditions: | Defaultfalse |
text_input · Required: messages
image_with_text · Required: messages with actual image content blocks
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, messages |
Parameteroptional | Contractstream |
Parametermaterial_types | Contracttext, image |
Parameterconditions | ContractUse this exact Ailoot routing selector., Image content is carried by this protocol where the exact selected model supports vision. Protocol admission does not establish image capability for every model. |
Method aliases: /chat/completions
Lifecycle: synchronous_or_streamed
Tariff references do not add request options. Supported parameters are listed for the selected method.
| Configuration | Rate schedule | Charge |
|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens $0 / 1K tokens Output · Output tokens $0 / 1K tokens Input · Cache read $0 / 1K tokens Input · Cache write $0 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "glm-4.1v-thinking-flash", "messages": [{"role": "user", "content": "Explain how a rainbow forms."}]}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\nJSON or SSE
Keep every complete returned response, file and content part.
Retain every content block, tool-call ID, thinking signature when returned, all SSE deltas and complete usage. A first text fragment is not the whole result.
Keep the original X-Client-Request-ID, response and headers. An unknown or result_pending_check outcome does not authorize a second creation.
| Field | Type |
|---|---|
Fieldchoices[] | Typeobject |
Fieldusage | Typeobject |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionA required field, model selector, type or input representation is invalid. | Next stepInspect the returned validation detail before preparing a separate request. |
Response | ConditionThe original request or result is unknown or requires a check. | Next stepKeep original identifiers and headers; read only supported status/library records. Do not submit creation again. |
Ailoot Ultra glm-4.1v-thinking-flash
/chat/completions
glm-4.1v-thinking-flashGLM-4.1V-Thinking-Flash is Zhipu’s visual reasoning model for chart analysis, scientific diagrams, document images and interface questions.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
GLM-4.1V-Thinking-Flash combines visual understanding with built-in reasoning. Zhipu describes the model for interpreting images and document pages, including charts, mathematical problems, interface structure and visual grounding. Its purpose is to connect what appears in the material with an explanation of the answer.
For a chart, preserve the axis labels, legend and units, then name the comparison or calculation. For a diagram, provide the problem statement and readable annotations. For an interface, identify the user’s goal and the controls or layout to examine. These details help distinguish a visible observation from an assumption.
Request a chart interpretation, a worked solution, a description of the relevant interface elements or a frontend implementation brief. Keep the source image with the answer, and check the labels, quantities and locations that the result depends on.
Through Ailoot, use the exact model ID in /v1/chat/completions and keep the image with its question in the conversation. The image content form uses image_url; supported image sources can carry an image address or base64 data URI. Collect the full JSON answer or all SSE segments when stream is enabled, and retain usage with the completed result.
POST /v1/messagestext, imagejson, sse| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits glm-4.1v-thinking-flash Conditions: Use this exact Ailoot routing selector. | Default— |
Fieldmessages | Typearray | RequirementRequired | Values & limits Conditions: | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits Conditions: | Defaultfalse |
Fieldmax_tokens | Typeinteger | RequirementRequired | Values & limits Minimum: 1 Conditions: | Default— |
text_input · Required: messages
image_with_text · Required: messages with actual image content blocks
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, messages, max_tokens |
Parameteroptional | Contractstream |
Parametermaterial_types | Contracttext, image |
Parameterconditions | ContractUse this exact Ailoot routing selector., Image content is carried by this protocol where the exact selected model supports vision. Protocol admission does not establish image capability for every model. |
Lifecycle: synchronous_or_streamed
Tariff references do not add request options. Supported parameters are listed for the selected method.
| Configuration | Rate schedule | Charge |
|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens $0 / 1K tokens Output · Output tokens $0 / 1K tokens Input · Cache read $0 / 1K tokens Input · Cache write $0 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "glm-4.1v-thinking-flash", "messages": [{"role": "user", "content": "Explain how a rainbow forms."}], "max_tokens": 256}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\nJSON or SSE
Keep every complete returned response, file and content part.
Retain every content block, tool-call ID, thinking signature when returned, all SSE deltas and complete usage. A first text fragment is not the whole result.
Keep the original X-Client-Request-ID, response and headers. An unknown or result_pending_check outcome does not authorize a second creation.
| Field | Type |
|---|---|
Fieldcontent[] | Typeobject |
Fieldusage | Typeobject |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionA required field, model selector, type or input representation is invalid. | Next stepInspect the returned validation detail before preparing a separate request. |
Response | ConditionThe original request or result is unknown or requires a check. | Next stepKeep original identifiers and headers; read only supported status/library records. Do not submit creation again. |
Ailoot Ultra glm-4.1v-thinking-flash
/chat/completions