Qwen3 235B A22B Thinking 2507

• GPQA DiamondVery hard multiple-choice questions in biology, physics and chemistry, written by PhD experts. Random guessing scores 25%.80.1%#65 of 116
• AIME mathCompetition-level math problems in the style of the American Invitational Mathematics Examination. Share solved.86.7%#53 of 112
• SimpleQA VerifiedShort factual questions. Measures how often the model gets facts right instead of making something up.40.4%#39 of 69

Benchmark data: Epoch AI, licensed CC BY 4.0

Companies that serve this model through an API: 3. Prices per million tokens, cheapest first.

Availability and prices come from OpenRouter’s public API and are refreshed daily. Uptime is the share of successful requests over the last 24 hours. Some providers run a compressed version of open models (fp8, int4), which is cheaper but can be slightly less accurate.

Call Qwen3 235B A22B Thinking 2507 through OpenRouter’s OpenAI-compatible API: create a key on openrouter.ai, then run one of these examples.

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen/qwen3-235b-a22b-thinking-2507", "messages": [{"role": "user", "content": "Hello! What can you do?"}]}'

import os
from openai import OpenAI

client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=os.environ["OPENROUTER_API_KEY"])
reply = client.chat.completions.create(
    model="qwen/qwen3-235b-a22b-thinking-2507",
    messages=[{"role": "user", "content": "Hello! What can you do?"}],
)
print(reply.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://openrouter.ai/api/v1", apiKey: process.env.OPENROUTER_API_KEY });
const reply = await client.chat.completions.create({
  model: "qwen/qwen3-235b-a22b-thinking-2507",
  messages: [{ role: "user", content: "Hello! What can you do?" }],
});
console.log(reply.choices[0].message.content);

The same code works with every model on this site: only the model ID changes. Many labs also offer their own API and SDK.

• 1,000 chat replies

  ≈ 500 tokens in, 300 out each
  $0.805
• Summarise a 100-page document

  ≈ 50,000 tokens in, 1,000 out
  $0.014
• An app with 10,000 requests a day for a month

  ≈ 1,000 tokens in, 400 out each
  $345

Cost calculator →

• Ars TechnicaSep 28, 2026

  Experts worry about Nvidia's AI chip sales in China and influence over Trump

• AWS Machine LearningOfficialSep 28, 2026

  Build real-time voice applications with vLLM-Omni on SageMaker AI – Part 1

• Simon WillisonSep 27, 2026

  2026 in LLMs (so far)

How much does Qwen3 235B A22B Thinking 2507 cost?

Qwen3 235B A22B Thinking 2507 costs $0.23 per million input tokens and $2.30 per million output tokens through the API. For example, 1,000 chat replies of about 500 tokens in and 300 out cost around $0.805.

What is the context window of Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 can read up to 131,072 tokens in one request, about 246 pages of text. It can write up to 117,964 tokens in a single answer.

Is Qwen3 235B A22B Thinking 2507 open source?

Yes. Its weights are published (Qwen/Qwen3-235B-A22B-Thinking-2507), so you can download it and run it on your own hardware, or use it through one of 3 API providers.

Who makes Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 is made by Alibaba Qwen. It became available through the API on July 25, 2025.

How good is Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 has an overall index of 143.9 in Epoch AI’s independent tests, ranking #80 of 136 models we track.

Can Qwen3 235B A22B Thinking 2507 read images?

No. Qwen3 235B A22B Thinking 2507 only accepts text as input.

What are the alternatives to Qwen3 235B A22B Thinking 2507?

Models with a similar price from other companies include DeepSeek V4 Flash Vision Exp, Gemini 3.1 Flash Lite and Trinity Large Thinking. You can compare them side by side on this page.