Mixtral Turbo 1.5B on MATH-500: score, rank and what it means
Mixtral Turbo 1.5B scores 44.2 on MATH-500, placing it #581 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Mixtral Turbo 1.5B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 3 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 4 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
| 5 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 8 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 9 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 10 | Claude Opus 4.5 Turbo | Anthropic | 2000000 | $19.57 | 85.7 |
What this score means
On MATH-500, Mixtral Turbo 1.5B sits at #581 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 52.5 points. The median model in this index scores 76.0, which puts Mixtral Turbo 1.5B below the midpoint.
Together AI models average 66.4 on this benchmark. Mixtral Turbo 1.5B is 22.2 points below that provider line, so it is a weaker result than the average Together AI model.
Among small open-weight models, the average is 53.7. Mixtral Turbo 1.5B is 9.5 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 44.2 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 $0.31 per million input tokens, Mixtral Turbo 1.5B is below the median input price of $4.00 across the 600 models scored on MATH-500. 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 |
|---|---|---|---|---|
| Yi-Large 1.5B | 01.AI | 8192 | $0.42 | 46.8 |
| StableLM 2 8B | Stability AI | 32768 | $0.38 | 47.0 |
| SmolLM3 7B | Hugging Face | 16384 | $0.19 | 44.3 |
| SmolLM3 8B | Hugging Face | 32768 | $0.21 | 44.0 |
| Mixtral Turbo 1.5B | Together AI | 4096 | $0.31 | 47.6 |
| Mixtral Groq 1.5B | Groq | 4096 | $0.34 | 46.1 |
| DBRX 1.5B | Databricks | 16384 | $0.32 | 47.0 |
Other benchmarks for Mixtral Turbo 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 55.1 | 572 | 5th | |
| GPQA Diamond | 45.3 | 565 | 6th | |
| SWE-bench Verified | 30.5 | 581 | 3th | |
| HumanEval | 51.5 | 561 | 7th | |
| AIME 2025 | 34.0 | 573 | 5th | |
| LiveCodeBench | 34.9 | 571 | 5th | |
| IFEval | 58.5 | 581 | 3th | |
| TruthfulQA | 54.1 | 578 | 4th | |
| HellaSwag | 67.0 | 563 | 6th | |
| MMMU | 48.5 | 559 | 7th | |
| Arena Elo | 1178.9 | 577 | 4th |
FAQ
What score does Mixtral Turbo 1.5B get on MATH-500?
Mixtral Turbo 1.5B scores 44.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Mixtral Turbo 1.5B rank on MATH-500?
It ranks #581 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 96.7.
Is Mixtral Turbo 1.5B good at MATH-500?
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 MATH-500 score calculated?
MATH-500 is a mathematics 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 1.5B cost?
Mixtral Turbo 1.5B costs $0.31 per million input tokens and $1.19 per million output tokens.