Commonsense · Mistral AI

Mixtral 7B on HellaSwag: score, rank and what it means

Mixtral 7B scores 70.3 on HellaSwag, placing it #531 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
70.3
0–100 scale
Rank
#531
of 600
Percentile
12th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
25.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Mixtral 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Mixtral 7B sits at #531 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 25.8 points. The median model in this index scores 83.6, which puts Mixtral 7B below the midpoint.

Mistral AI models average 79.8 on this benchmark. Mixtral 7B is 9.5 points below that provider line, so it is a weaker result than the average Mistral AI model.

Among small open-weight models, the average is 70.2. Mixtral 7B is 0.1 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 70.3 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 $0.70 per million input tokens, Mixtral 7B is below the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DBRX 7B Databricks 8192 $0.65 51.9
Kimi K1.5 1.5B Moonshot AI 4096 $0.75 53.2
Llama 3.3 Groq 7B Groq 16384 $1.01 56.7
DBRX 8B Databricks 4096 $0.82 54.1
Mixtral 7B Mistral AI 16384 $0.70 54.1
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
Mixtral Turbo 8B Together AI 4096 $0.75 54.1

Other benchmarks for Mixtral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 61.8 505 16th
GPQA Diamond 50.8 513 15th
SWE-bench Verified 38.7 532 11th
HumanEval 56.8 532 11th
MATH-500 51.6 545 9th
AIME 2025 42.3 530 12th
LiveCodeBench 41.7 528 12th
IFEval 66.5 512 15th
TruthfulQA 59.9 531 12th
MMMU 54.6 502 16th
Arena Elo 1216.6 537 11th

FAQ

What score does Mixtral 7B get on HellaSwag?

Mixtral 7B scores 70.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mixtral 7B rank on HellaSwag?

It ranks #531 of 600 models, in the 12th percentile. The leader is GPT-5.2 Max at 96.1.

Is Mixtral 7B good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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 7B cost?

Mixtral 7B costs $0.70 per million input tokens and $3.13 per million output tokens.

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