Alibaba Qwen: Qwen3 VL 30B A3B Thinking

Qwen3 VL 30B A3B Thinking is Alibaba Qwen's open multimodal model, released 2025-10, that pairs flagship-level text generation with visual understanding for images and videos. Its thinking mode targets STEM, math, and complex reasoning, while agentic strengths include GUI automation and visual coding from sketches to debugged UI.

Modalities
inTextinImageoutText
Price / 1M
$67.50 / $67.50
Context
262K
Released
Oct 6, 2025
Knowledge cutoff
Mar 31, 2025

Channels

Every channel serves the same model, but they differ in price and stability. On each API key in the Platform, you pick a primary and a backup channel per vendor, and each billing line shows which channel served the request.

Provider
Discount
Input /M
Output /M
Cache read /M
Cache write 5m /M
Cache write 1h /M
Defaultstable
+10365%
$67.50
$67.50
—
—
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Capabilities

ReasoningVisionTool useLong contextStructured output

Parameters

Request parameters this model accepts through the API.

frequency_penaltyinclude_reasoningmax_tokensreasoningresponse_formatstructured_outputstemperaturetool_choicetoolstop_ktop_p

Cost calculator

Pick a channel and a usage scenario, then drag the sliders to match your workload. Each scenario assumes a different prompt-cache hit rate.

Channel
Scenario
Unit $67.50 / $67.50 /1MDaily chat: 40% cache hit rate assumed · cache read $6.75 /1M
On MirAPI$7387.20/ moCreate an API key

Benchmarks

bar = score (0–100) · ▏ median

Scores come from vendor reports and public leaderboards, not private evals.

Intelligence Index
General ability
9.5
#131

Showcase

Every chat model gets the same three fixed prompts. Outputs are archived verbatim, so you can copy a prompt and reproduce the result.

Task prompt · identical for all models
Build a single-file HTML page using three.js from a CDN: a low-poly planet with a tilted ring of ~200 orbiting particles, a soft key light plus rim light, slow auto-rotation, and drag-to-orbit controls. No build tools — one file only.
Archived output
Archive not published yet

Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.

Quick start

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.mirapi.ai/v1",   # changed
    api_key=os.environ["MIRAPI_API_KEY"],   # changed
)

resp = client.chat.completions.create(
    model="qwen3-vl-30b-a3b-thinking",
    messages=[{"role": "user", "content": "Hello"}],
)
Wire Qwen3 VL 30B A3B Thinking into your product

1M free tokens to start, no card required. It’s OpenAI-compatible, so you only change the base URL.

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