Qwen3-Coder Chat on LiveCodeBench: score, rank and what it means
Qwen3-Coder Chat scores 68.9 on LiveCodeBench, placing it #211 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.
Score distribution
The chart shows the top 10 models on LiveCodeBench, with Qwen3-Coder Chat highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 2 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 3 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | Grok 4 Turbo | xAI | 1000000 | $19.21 | 86.7 |
| 6 | GPT-5.1 Turbo | OpenAI | 2000000 | $19.19 | 86.1 |
| 7 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 8 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 9 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On LiveCodeBench, Qwen3-Coder Chat sits at #211 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 16.2 points. The median model in this index scores 64.7, which puts Qwen3-Coder Chat above the midpoint.
Alibaba Cloud models average 64.0 on this benchmark. Qwen3-Coder Chat is 4.9 points above that provider line, so it is a stronger result than the average Alibaba Cloud model.
Among coding models, the average is 59.3. Qwen3-Coder Chat is 9.6 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 68.9 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $4.59 per million input tokens, Qwen3-Coder Chat is above the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3 Hyperbolic Chat | Hyperbolic | 200000 | $3.64 | 75.1 |
| Llama 3 Hyperbolic Instruct | Hyperbolic | 200000 | $3.79 | 76.2 |
| GLM-4.5 Chat | Zhipu AI | 65536 | $4.53 | 78.3 |
| Phi-4 Chat | Microsoft | 65536 | $3.66 | 74.7 |
| Qwen3-Coder Chat | Alibaba Cloud | 128000 | $4.59 | 78.4 |
| ERNIE 4.0 Pro | Baidu | 200000 | $12.58 | 77.5 |
| QwQ Chat | Alibaba Cloud | 65536 | $4.28 | 78.2 |
Other benchmarks for Qwen3-Coder Chat
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 79.4 | 201 | 67th | |
| GPQA Diamond | 72.4 | 213 | 65th | |
| SWE-bench Verified | 69.5 | 122 | 80th | |
| HumanEval | 82.9 | 161 | 73th | |
| MATH-500 | 85.2 | 106 | 82th | |
| AIME 2025 | 74.0 | 183 | 70th | |
| IFEval | 85.0 | 193 | 68th | |
| TruthfulQA | 81.3 | 146 | 76th | |
| HellaSwag | 88.0 | 142 | 76th | |
| MMMU | 76.2 | 135 | 78th | |
| Arena Elo | 1411.0 | 182 | 70th |
FAQ
What score does Qwen3-Coder Chat get on LiveCodeBench?
Qwen3-Coder Chat scores 68.9 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does Qwen3-Coder Chat rank on LiveCodeBench?
It ranks #211 of 600 models, in the 65th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is Qwen3-Coder Chat good at LiveCodeBench?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the LiveCodeBench score calculated?
LiveCodeBench is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Qwen3-Coder Chat cost?
Qwen3-Coder Chat costs $4.59 per million input tokens and $21.05 per million output tokens.