Qwen3 Chat: pricing, context window and benchmarks
Qwen3 Chat is a multimodal model from Alibaba Cloud. It offers a 128,000-token context window, costs $4.75 per million input tokens and $17.42 per million output tokens, and averages 79.1 across the index's benchmark suite.
Pricing
Qwen3 Chat costs $4.75 per million input tokens and $17.42 per million output tokens. A blended 3:1 input-to-output mix works out to about $7.92 per million tokens. Cached input is listed at $0.65 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $4.75 | per 1M tokens |
| Output | $17.42 | per 1M tokens |
| Cached input | $0.65 | per 1M tokens |
| Blended 3:1 | $7.92 | estimate per 1M tokens |
| 1M in + 1M out | $22.17 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 83.4 | 98 | 84th | |
| GPQA Diamond | 73.9 | 173 | 71th | |
| SWE-bench Verified | 68.5 | 133 | 78th | |
| HumanEval | 83.9 | 136 | 77th | |
| MATH-500 | 81.4 | 180 | 70th | |
| AIME 2025 | 73.8 | 190 | 68th | |
| LiveCodeBench | 72.2 | 144 | 76th | |
| IFEval | 87.5 | 118 | 80th | |
| TruthfulQA | 81.3 | 145 | 76th | |
| HellaSwag | 86.5 | 194 | 68th | |
| MMMU | 77.3 | 110 | 82th | |
| Arena Elo | 1417.2 | 160 | 73th |
What Qwen3 Chat is good for
Qwen3 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.75 per million input tokens, it sits in the mid-range of the index, and the 128,000-token context window is enough for large files and multi-file diffs.
Strengths
- Large 128,000-token context window for long documents and agent traces.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
- Coding benchmarks are a relative strength within its tier.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 4 Maverick Base | Meta AI | 128000 | $4.68 | 79.1 |
| Llama 4 Scout Instruct | Meta AI | 32768 | $4.59 | 79.1 |
| Mistral Large 3 Chat | Mistral AI | 1000000 | $4.90 | 79.1 |
| Qwen3 Chat | Alibaba Cloud | 128000 | $4.75 | 79.1 |
| Sonar Pro | Perplexity | 128000 | $13.01 | 79.1 |
| Claude Opus 4.5 Mini | Anthropic | 65536 | $12.72 | 79.0 |
FAQ
How much does Qwen3 Chat cost?
Qwen3 Chat is listed at $4.75 per million input tokens and $17.42 per million output tokens. Cached input is $0.65 per million tokens. A blended 3:1 input-to-output mix is about $7.92 per million tokens.
What is the context window of Qwen3 Chat?
Qwen3 Chat has a context window of 128,000 tokens and can emit up to 65,536 output tokens per request in this index.
Is Qwen3 Chat open weights?
Yes. Qwen3 Chat is listed as an open-weight model under a open weights licence.
How does Qwen3 Chat score on benchmarks?
Qwen3 Chat averages 79.1 across the scored benchmarks in this index, ranking #147 of 600 models. Its strongest relative result is Arena Elo at 1417.2.
What is Qwen3 Chat best for?
Qwen3 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.75 per million input tokens, it sits in the mid-range of the index, and the 128,000-token context window is enough for large files and multi-file diffs.