Reasoning · Mistral AI

Mixtral Instruct on GPQA Diamond: score, rank and what it means

Mixtral Instruct scores 67.6 on GPQA Diamond, placing it #320 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
67.6
0–100 scale
Rank
#320
of 600
Percentile
47th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
19.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Mixtral Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Mixtral Instruct sits at #320 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 19.4 points. The median model in this index scores 68.8, which puts Mixtral Instruct below the midpoint.

Mistral AI models average 63.3 on this benchmark. Mixtral Instruct is 4.3 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 73.5. Mixtral Instruct is 5.9 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 67.6 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 $3.35 per million input tokens, Mixtral Instruct is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemma 3 Chat Google DeepMind 65536 $3.74 74.5
Llama 3 Baseten Base Baseten 16384 $3.16 72.4
Llama 3 Replicate Replicate 200000 $3.75 75.7
Fusion Pro OpenRouter 65536 $8.69 72.2
Mixtral Instruct Mistral AI 65536 $3.35 72.9
DBRX Databricks 65536 $3.29 73.3
Firefunction Turbo Fireworks AI 32768 $8.44 70.7

Other benchmarks for Mixtral Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.0 279 54th
SWE-bench Verified 61.0 299 50th
HumanEval 78.2 286 52th
MATH-500 75.6 312 48th
AIME 2025 69.0 282 53th
LiveCodeBench 66.2 271 55th
IFEval 79.8 336 44th
TruthfulQA 75.4 322 46th
HellaSwag 82.0 348 42th
MMMU 70.2 293 51th
Arena Elo 1362.7 338 44th

FAQ

What score does Mixtral Instruct get on GPQA Diamond?

Mixtral Instruct scores 67.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Mixtral Instruct rank on GPQA Diamond?

It ranks #320 of 600 models, in the 47th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Mixtral Instruct good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Instruct cost?

Mixtral Instruct costs $3.35 per million input tokens and $18.19 per million output tokens.

Related