Any Llm API Documentation

Any Llm API Documentation

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Any LLM is a versatile large language model for text generation, comprehension, and diverse NLP tasks such as chat and summarization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Any LLM is a unified text-generation endpoint. Use one request format to run a curated set of language models.

Supported models

  • google/gemini-2.5-flash
  • google/gemini-2.5-pro
  • google/gemini-3-flash-preview
  • qwen/qwen3.6-35b-a3b
  • qwen/qwen3.6-27b
  • qwen/qwen3.7-flash

Model selection and fallback

Pass one of the exact model IDs above in the model field. If model is omitted, the schema default is used. If a supplied model ID is not in the supported list, the request is automatically routed to qwen/qwen3.7-flash.

The supported model list and fallback policy for this endpoint may change at any time. Check the current model selector or API schema before relying on a specific model.

Parameters

ParameterRequiredDescription
promptYesUser prompt or instruction.
system_promptNoSystem instructions, up to 10,000 characters.
modelNoExact supported model ID. Unknown IDs use the fallback above.
reasoningNoInclude supported reasoning content in the final answer.
priorityNolatency or throughput.
temperatureNoSampling temperature from 0 to 2.
max_tokensNoMaximum generated tokens, subject to the selected model context limit.
enable_sync_modeNoAttempt to wait for the result in the same API response.

Notes

  • Model capabilities, context limits, latency, and output behavior vary by provider.
  • Processing time varies with the selected model and request complexity.
  • Requests must comply with the applicable usage guidelines.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "reasoning": false,
  "priority": "latency",
  "model": "google/gemini-2.5-flash"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/any-llm" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
system_promptstringNo--System prompt to provide context or instructions to the model
reasoningbooleanNofalse-Should reasoning be the part of the final answer.
prioritystringNolatencythroughput, latencyThroughput is the default and is recommended for most use cases. Latency is recommended for use cases where low latency is important.
temperaturenumberNo-0 ~ 2This setting influences the variety in the model's responses. Lower values lead to more predictable and typical responses, while higher values encourage more diverse and less common responses. At 0, the model always gives the same response for a given input.
max_tokensintegerNo-1 ~ ∞This sets the upper limit for the number of tokens the model can generate in response. It won't produce more than this limit. The maximum value is the context length minus the prompt length.
modelstringNogoogle/gemini-2.5-flash-Model ID to use. Supported values are shown in the model selector. If a supplied model ID is not listed, the request falls back to qwen/qwen3.7-flash. The supported model list and fallback policy for this endpoint may change at any time.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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