Qwen: Qwen3 235B A22B Instruct 2507

Qwen: Qwen3 235B A22B Instruct 2507

qwen · Released Jul 21, 2025
Intelligence #100 / 699
53.2 our score
Speed #221 / 320
59.3 tok/s
Input Price #213 / 714
$0.090 per 1M tokens
Output Price #296 / 714
$0.550 per 1M tokens
Context #195 / 714
262,144 tokens

Analysis Summary

Qwen3 235B A22B Instruct 2507 is a large open model with a strong mathematical profile and useful breadth across coding, instruction following, and long-context tasks. Its 262K context window supports substantial documents and code inputs, while tool use and function calling make it suitable for structured workflows. The text-only interface keeps the model focused on language and reasoning tasks.

It is a good fit for mathematical analysis, technical content, code generation, SEO workflows, and tool-connected automation where price efficiency matters. The broader intelligence and agentic results are not at flagship level, and the terminal performance suggests caution with autonomous software operations. Instruction following is usable but not consistently reliable enough for every client-facing workflow.

Low pricing improves its role as a volume model. Adopt it for cost-sensitive technical and structured workloads, with human review or a stronger model for complex decisions.

Assessed August 9, 2026

Editorial notes

Qwen3 235B A22B Instruct 2507 delivers strong mathematical results, a 262K context window, tool use, function calling, and low pricing. General reasoning, coding reliability, and agentic execution remain below flagship standards.

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

DFO Verdict

Qwen3 235B A22B Instruct 2507 delivers strong mathematical results, a 262K context window, tool use, function calling, and low pricing. General reasoning, coding reliability, and agentic execution remain below flagship standards.

#100 of 699 overall

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 #182 of 427 AI models we track for overall intelligence, #133 of 200 for coding, #49 of 182 for agentic tasks. Its 262K-token context window is larger than 73% 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 86% of models #100
Speed: faster than 31% of models #221
Price: cheaper than 70% of models #213
Context: larger than 73% of models #195
worst in fieldmedianbest in field
Price vs frontier peers · $ per 1M tokens
Qwen: Qwen3 235B A22B Instruct 2507 $0.09 in $0.55 out
Claude Opus 5 $5.00 in $25.00 out
SpaceXAI: Grok 4.6 $2.00 in $6.00 out
Qwen: Qwen3.8 Max $2.00 in $6.00 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.

Intelligence3.9Technical3.7Value8Content5.8
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 $0.000090
Output $0.55 $0.000550

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 714 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 $0.55 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 #133 of 200 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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