Mixtral Turbo on LiveCodeBench: score, rank and what it means
Mixtral Turbo scores 63.6 on LiveCodeBench, placing it #330 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 Mixtral Turbo 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, Mixtral Turbo sits at #330 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 21.5 points. The median model in this index scores 64.7, which puts Mixtral Turbo below the midpoint.
Together AI models average 54.9 on this benchmark. Mixtral Turbo is 8.7 points above that provider line, so it is a stronger result than the average Together AI model.
Among open-weight models, the average is 59.1. Mixtral Turbo is 4.5 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 63.6 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 $3.20 per million input tokens, Mixtral Turbo is below 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 |
|---|---|---|---|---|
| Firefunction Reasoning | Fireworks AI | 8192 | $9.08 | 72.5 |
| Firesearch Max | Fireworks AI | 8192 | $7.80 | 69.9 |
| Mistral Small 3 Base | Mistral AI | 16384 | $3.19 | 72.7 |
| Phi-4 Base | Microsoft | 32768 | $3.15 | 71.2 |
| Mixtral Turbo | Together AI | 65536 | $3.20 | 72.4 |
| Llama 3 Anyscale Base | Anyscale | 65536 | $3.23 | 72.9 |
| Llama 3 DeepInfra Base | DeepInfra | 16384 | $2.95 | 71.8 |
Other benchmarks for Mixtral Turbo
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 77.6 | 256 | 57th | |
| GPQA Diamond | 69.5 | 279 | 54th | |
| SWE-bench Verified | 57.8 | 360 | 40th | |
| HumanEval | 77.7 | 295 | 51th | |
| MATH-500 | 75.4 | 315 | 48th | |
| AIME 2025 | 67.9 | 297 | 51th | |
| IFEval | 78.7 | 360 | 40th | |
| TruthfulQA | 74.0 | 351 | 42th | |
| HellaSwag | 82.5 | 335 | 44th | |
| MMMU | 71.5 | 258 | 57th | |
| Arena Elo | 1364.3 | 335 | 44th |
FAQ
What score does Mixtral Turbo get on LiveCodeBench?
Mixtral Turbo scores 63.6 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does Mixtral Turbo rank on LiveCodeBench?
It ranks #330 of 600 models, in the 45th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is Mixtral Turbo good at LiveCodeBench?
It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 Mixtral Turbo cost?
Mixtral Turbo costs $3.20 per million input tokens and $13.66 per million output tokens.