Mathematics · Together AI

Mixtral Turbo on MATH-500: score, rank and what it means

Mixtral Turbo scores 75.4 on MATH-500, placing it #315 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
75.4
0–100 scale
Rank
#315
of 600
Percentile
48th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
21.3
points

Score distribution

The chart shows the top 10 models on MATH-500, with Mixtral Turbo highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg 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 sits at #315 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 21.3 points. The median model in this index scores 76.0, which puts Mixtral Turbo below the midpoint.

Together AI models average 66.4 on this benchmark. Mixtral Turbo is 9.0 points above that provider line, so it is a stronger result than the average Together AI model.

Among open-weight models, the average is 70.8. Mixtral Turbo is 4.6 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 75.4 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Lambda Chat Lambda 32768 $3.73 74.7
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Seed-OSS Chat ByteDance 65536 $3.49 74.4
Mixtral Turbo Together AI 65536 $3.20 72.4
Phi-3.5 Microsoft 16384 $2.81 70.9
Command A Mini Cohere 8192 $8.12 71.0

Other benchmarks for Mixtral Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.6 256 57th
GPQA Diamond 69.5 279 54th
SWE-bench Verified 57.8 360 40th
HumanEval 77.7 295 51th
AIME 2025 67.9 297 51th
LiveCodeBench 63.6 330 45th
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 MATH-500?

Mixtral Turbo scores 75.4 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Mixtral Turbo rank on MATH-500?

It ranks #315 of 600 models, in the 48th percentile. The leader is GPT-5.2 Max at 96.7.

Is Mixtral Turbo 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 cost?

Mixtral Turbo costs $3.20 per million input tokens and $13.66 per million output tokens.

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