Qwen: Qwen3 235B A22B Instruct 2507

Qwen: Qwen3 235B A22B Instruct 2507

qwen · Released Jul 21, 2025
Intelligence #98 / 756
54.7 our score
Speed #233 / 332
59.3 tok/s
Input Price #232 / 772
$0.088 per 1M tokens
Output Price #276 / 772
$0.350 per 1M tokens
Context #226 / 772
262,144 tokens

Analysis Summary

Qwen3 235B A22B Instruct 2507 is a large open-weight-oriented model with a 262K context window, tool use, and function calling. Its mathematics results are particularly strong, while coding and agentic results support practical technical automation. Low input and output prices make it attractive for substantial workloads.

The model fits code assistance, structured research, SEO generation, document analysis, and controlled tool-calling agents. Its context window can hold sizeable source collections, but the general reasoning and coding profile is below current flagship systems. Autonomous workflows should validate actions and outputs, especially when terminal operations or complex planning are involved.

Route high-volume technical and structured tasks to Qwen3 235B A22B when cost efficiency is important. Reserve premium models for final editorial judgement and difficult reasoning.

Assessed September 7, 2026

Editorial notes

Qwen3 235B A22B offers strong mathematics, a 262K context window, tool use, and function calling at very low pricing. It is a capable technical and automation choice, though coding and general reasoning trail current flagship systems.

Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?

DFO Verdict

Qwen3 235B A22B offers strong mathematics, a 262K context window, tool use, and function calling at very low pricing. It is a capable technical and automation choice, though coding and general reasoning trail current flagship systems.

#98 of 756 overall Up 10 this week

Benchmark scores

GPQA Diamond 79%
HLE 15%
MMLU Pro 84.3%
MATH 500 98.4%
AIME 94%
AIME 2025 91%
SciCode 42.4%
LiveCodeBench 78.8%
TerminalBench Hard 13.6%
τ²-Bench 53.2%
IFBench 51.2%
LCR 67%

Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.

19.6 Intelligence Index·22.1 Coding Index·33.4 Agentic Index·91 Math Index

How Qwen: Qwen3 235B A22B Instruct 2507 compares

Qwen: Qwen3 235B A22B Instruct 2507 ranks #139 of 437 AI models we track for overall intelligence, #141 of 209 for coding, #49 of 191 for agentic tasks. Its 262K-token context window is larger than 71% of the models we list. At $0.09 per million input tokens it is cheaper than 70% of comparable models.

Position in the field
Intelligence: smarter than 87% of models #98
Speed: faster than 30% of models #233
Price: cheaper than 70% of models #232
Context: larger than 71% of models #226
worst in fieldmedianbest in field
Price vs frontier peers · $ per 1M tokens
Qwen: Qwen3 235B A22B Instruct 2507 $0.09 in $0.35 out
OpenAI: GPT-6 Astra $10.00 in $50.00 out
Anthropic: Claude Fable 5.1 $10.00 in $50.00 out
Claude Opus 5 $5.00 in $25.00 out

Dark bar = input · light bar = output, scaled to the priciest peer.

Context window vs peers · tokens
Qwen: Qwen3 235B A22B Instruct 2507 262K

1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.

Intelligence3.9Technical3.7Value8Content6.5
Performance profile

Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.

Compare shapes side-by-side →

Pricing

Token Type Cost per 1M tokens Cost per 1K tokens
Input $0.09 $0.000088
Output $0.35 $0.000350

What would Qwen: Qwen3 235B A22B Instruct 2507 cost your business?

Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.

A website chatbot handling around 100 customer conversations a day, a few short messages each.

3,000
One request is one message, email, draft or automation call.
1,200 tokens

$0/mo Qwen: Qwen3 235B A22B Instruct 2507

Full calculator with 772 models → Price Calculator

DFO AI AUTOMATION

These numbers get smaller with the right architecture.

We route routine calls to cheap models and save Qwen: Qwen3 235B A22B Instruct 2507 for the hard ones. Most clients cut their estimate by 60-80%.

Talk to our team

About Qwen: Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,..

Frequently asked questions about Qwen: Qwen3 235B A22B Instruct 2507

How much does Qwen: Qwen3 235B A22B Instruct 2507 cost?

Qwen: Qwen3 235B A22B Instruct 2507 costs $0.09 per million input tokens and $0.35 per million output tokens.

What is the context window of Qwen: Qwen3 235B A22B Instruct 2507?

Qwen: Qwen3 235B A22B Instruct 2507 has a context window of 262,144 tokens (262K).

Is Qwen: Qwen3 235B A22B Instruct 2507 good for coding?

On our coding benchmark index, Qwen: Qwen3 235B A22B Instruct 2507 ranks #141 of 209 models, placing it in the broader range of the field for code generation and debugging.

What can Qwen: Qwen3 235B A22B Instruct 2507 do?

Qwen: Qwen3 235B A22B Instruct 2507 supports tool use and function calling.

Who created Qwen: Qwen3 235B A22B Instruct 2507?

Qwen: Qwen3 235B A22B Instruct 2507 is developed by Qwen and was released on July 21, 2025.

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