Author's Description
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, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement "thinking mode" (<think> blocks). Compared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
Qwen3-235B-A22B-Instruct-2507 demonstrates moderate speed performance, ranking in the 34th percentile across various benchmarks. It generally offers cost-effective solutions, placing in the 61st percentile for pricing. A standout feature is its exceptional reliability, boasting a 98% success rate, indicating consistent and usable responses. In terms of specific benchmarks, the model exhibits strong capabilities in Coding (85.9% accuracy, 68th percentile) and Reasoning (75.0% accuracy, 73rd percentile). It achieves near-perfect accuracy in General Knowledge (99.5%, 84th percentile) and a perfect 100% in Ethics, notably being the most accurate model at its price point and among models of similar speed. However, its performance in Instruction Following (39.7% accuracy, 39th percentile) and Email Classification (94.0% accuracy, 32nd percentile) is less competitive, suggesting areas for improvement in precision for complex multi-step instructions and classification tasks despite high raw accuracy in the latter. Overall, the model excels in knowledge-intensive and logical reasoning tasks, showcasing its strength in complex problem-solving and ethical considerations.
Model Pricing
Current Pricing
Feature | Price (per 1M tokens) |
---|---|
Prompt | $0.078 |
Completion | $0.312 |
Price History
Available Endpoints
Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
---|---|---|---|---|
Parasail
|
Parasail | qwen/qwen3-235b-a22b-07-25 | 262K | $0.078 / 1M tokens | $0.312 / 1M tokens |
DeepInfra
|
DeepInfra | qwen/qwen3-235b-a22b-07-25 | 262K | $0.13 / 1M tokens | $0.6 / 1M tokens |
Targon
|
Targon | qwen/qwen3-235b-a22b-07-25 | 262K | $0.078 / 1M tokens | $0.312 / 1M tokens |
Parasail
|
Parasail | qwen/qwen3-235b-a22b-07-25 | 262K | $0.15 / 1M tokens | $0.85 / 1M tokens |
Fireworks
|
Fireworks | qwen/qwen3-235b-a22b-07-25 | 262K | $0.22 / 1M tokens | $0.88 / 1M tokens |
Targon
|
Targon | qwen/qwen3-235b-a22b-07-25 | 262K | $0.12 / 1M tokens | $0.59 / 1M tokens |
Alibaba
|
Alibaba | qwen/qwen3-235b-a22b-07-25 | 131K | $0.7 / 1M tokens | $2.8 / 1M tokens |
Together
|
Together | qwen/qwen3-235b-a22b-07-25 | 262K | $0.2 / 1M tokens | $0.6 / 1M tokens |
Novita
|
Novita | qwen/qwen3-235b-a22b-07-25 | 262K | $0.078 / 1M tokens | $0.312 / 1M tokens |
GMICloud
|
GMICloud | qwen/qwen3-235b-a22b-07-25 | 131K | $0.17 / 1M tokens | $1.09 / 1M tokens |
Novita
|
Novita | qwen/qwen3-235b-a22b-07-25 | 262K | $0.15 / 1M tokens | $0.8 / 1M tokens |
Cerebras
|
Cerebras | qwen/qwen3-235b-a22b-07-25 | 131K | $0.6 / 1M tokens | $1.2 / 1M tokens |
Chutes
|
Chutes | qwen/qwen3-235b-a22b-07-25 | 262K | $0.078 / 1M tokens | $0.312 / 1M tokens |
Nebius
|
Nebius | qwen/qwen3-235b-a22b-07-25 | 262K | $0.2 / 1M tokens | $0.6 / 1M tokens |
BaseTen
|
BaseTen | qwen/qwen3-235b-a22b-07-25 | 262K | $0.22 / 1M tokens | $0.8 / 1M tokens |
AtlasCloud
|
AtlasCloud | qwen/qwen3-235b-a22b-07-25 | 262K | $0.35 / 1M tokens | $1.2 / 1M tokens |
Benchmark Results
Benchmark | Category | Reasoning | Free | Executions | Accuracy | Cost | Duration |
---|
Other Models by qwen
|
Released | Params | Context |
|
Speed | Ability | Cost |
---|---|---|---|---|---|---|---|
Qwen: Qwen3 30B A3B Instruct 2507 | Jul 29, 2025 | 30B | 131K |
Text input
Text output
|
★★★★ | ★★★★ | $$$ |
Qwen: Qwen3 235B A22B Thinking 2507 | Jul 25, 2025 | 235B | 131K |
Text input
Text output
|
★ | ★★★★ | $$$$$ |
Qwen: Qwen3 Coder | Jul 22, 2025 | 480B | 1M |
Text input
Text output
|
★★★★ | ★★★ | $$$ |
Qwen: Qwen3 30B A3B | Apr 28, 2025 | 30B | 40K |
Text input
Text output
|
★ | ★★★★★ | $$$$ |
Qwen: Qwen3 8B | Apr 28, 2025 | 8B | 128K |
Text input
Text output
|
★ | ★★★ | $$$ |
Qwen: Qwen3 14B | Apr 28, 2025 | 14B | 40K |
Text input
Text output
|
★★ | ★★★★★ | $$$ |
Qwen: Qwen3 32B | Apr 28, 2025 | 32B | 40K |
Text input
Text output
|
★ | ★★★★★ | $$$ |
Qwen: Qwen3 235B A22B | Apr 28, 2025 | 235B | 40K |
Text input
Text output
|
★ | ★★★★ | $$$$ |
Qwen: Qwen2.5 VL 32B Instruct | Mar 24, 2025 | 32B | 128K |
Text input
Image input
Text output
|
★★ | ★★★ | $$$ |
Qwen: QwQ 32B | Mar 05, 2025 | 32B | 131K |
Text input
Text output
|
★ | ★★★ | $$$ |
Qwen: Qwen VL Plus | Feb 04, 2025 | — | 7K |
Text input
Image input
Text output
|
★★★★ | ★★ | $$$ |
Qwen: Qwen VL Max | Feb 01, 2025 | — | 7K |
Text input
Image input
Text output
|
★★★★★ | ★★★ | $$$$ |
Qwen: Qwen-Turbo | Feb 01, 2025 | — | 1M |
Text input
Text output
|
★★★★★ | ★★★★ | $$ |
Qwen: Qwen2.5 VL 72B Instruct | Feb 01, 2025 | 72B | 32K |
Text input
Image input
Text output
|
★★★★ | ★★★★ | $$ |
Qwen: Qwen-Plus | Feb 01, 2025 | — | 131K |
Text input
Text output
|
★★★ | ★★★★ | $$$ |
Qwen: Qwen-Max | Feb 01, 2025 | — | 32K |
Text input
Text output
|
★★★ | ★★★★ | $$$$ |
Qwen: QwQ 32B Preview | Nov 27, 2024 | 32B | 32K |
Text input
Text output
|
— | ★ | $$ |
Qwen2.5 Coder 32B Instruct | Nov 11, 2024 | ~500B | 32K |
Text input
Text output
|
★★★★★ | ★★★★★ | $ |
Qwen2.5 7B Instruct | Oct 15, 2024 | ~500B | 32K |
Text input
Text output
|
★ | ★★★ | $$ |
Qwen2.5 72B Instruct | Sep 18, 2024 | ~500B | 32K |
Text input
Text output
|
★★★ | ★★★ | $$$ |
Qwen: Qwen2.5-VL 7B Instruct | Aug 27, 2024 | ~500B | 32K |
Text input
Image input
Text output
|
★★★ | ★★★ | $$$ |
Qwen 2 72B Instruct | Jun 06, 2024 | ~500B | 32K |
Text input
Text output
|
★★★★ | ★★ | $$$$ |