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Use any vision-language model from a curated catalogue, powered by OpenRouter, for flexible multimodal inference. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

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Any LLM Vision

Any LLM Vision is a unified vision-language endpoint. Send text and image URLs to a curated set of multimodal models through one request format.

Supported models

  • google/gemini-2.5-flash
  • google/gemini-2.5-pro
  • google/gemini-3.1-flash-lite
  • 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
promptYesQuestion or instruction about the supplied images.
imagesNoImage URL list, with at most 10 images per request.
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

  • Image understanding and supported media formats vary by model.
  • Processing time varies with the selected model, image count, and request complexity.
  • Requests must comply with the applicable usage guidelines.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Any Llm Vision API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/any-llm/vision with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Any Llm Vision below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "What is the meaning of life?",
    "images": [
        "https://d1q70pf5vjeyhc.cloudfront.net/media/92d2d4ca66f84793adcb20742b15d262/images/1753708615921599101_VpKMX8di.png"
    ],
    "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/vision" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; 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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$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
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/any-llm/vision";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "What is the meaning of life?",
        "images": [
                "https://d1q70pf5vjeyhc.cloudfront.net/media/92d2d4ca66f84793adcb20742b15d262/images/1753708615921599101_VpKMX8di.png"
        ],
        "reasoning": false,
        "priority": "latency",
        "model": "google/gemini-2.5-flash"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "What is the meaning of life?",
    "images": [
        "https://d1q70pf5vjeyhc.cloudfront.net/media/92d2d4ca66f84793adcb20742b15d262/images/1753708615921599101_VpKMX8di.png"
    ],
    "reasoning": False,
    "priority": "latency",
    "model": "google/gemini-2.5-flash"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/any-llm/vision", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Any Llm Vision API — Frequently asked questions

What is the Any Llm Vision API?

Any Llm Vision is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Use any vision-language model from a curated catalogue, powered by OpenRouter, for flexible multimodal inference. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Any Llm Vision API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/any-llm-vision.

How much does Any Llm Vision cost per run?

Any Llm Vision starts at $0.050 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Any Llm Vision accept?

Key inputs: `prompt`, `images`, `enable_sync_mode`, `max_tokens`, `model`, `priority`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/any-llm-vision.

How long does Any Llm Vision take to generate?

Median end-to-end generation time on WaveSpeedAI is around 9 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Any Llm Vision outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Any LLM Vision | Fast LLM API on WaveSpeedAI