Commonsense · Mistral AI

Mixtral 8B on HellaSwag: score, rank and what it means

Mixtral 8B scores 71.5 on HellaSwag, placing it #510 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
71.5
0–100 scale
Rank
#510
of 600
Percentile
15th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
24.6
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Mixtral 8B 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 8B sits at #510 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 24.6 points. The median model in this index scores 83.6, which puts Mixtral 8B below the midpoint.

Mistral AI models average 79.8 on this benchmark. Mixtral 8B is 8.3 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 8B is 1.3 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 71.5 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 $0.91 per million input tokens, Mixtral 8B 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
Nemotron 4 8B NVIDIA 4096 $1.06 57.9
Mixtral Groq 8B Groq 32768 $0.77 54.8
Yi-Lightning 7B 01.AI 32768 $1.00 55.9
Llama 3 Modal 8B Modal 32768 $0.98 56.6
Mixtral 8B Mistral AI 8192 $0.91 55.4
Llama 3 Baseten 7B Baseten 32768 $0.87 55.3
Llama 3 Baseten 8B Baseten 4096 $1.02 57.0

Other benchmarks for Mixtral 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.0 502 16th
GPQA Diamond 52.3 498 17th
SWE-bench Verified 41.1 510 15th
HumanEval 58.6 516 14th
MATH-500 56.3 504 16th
AIME 2025 44.3 504 16th
LiveCodeBench 41.9 526 12th
IFEval 68.4 484 19th
TruthfulQA 61.4 515 14th
MMMU 52.1 529 12th
Arena Elo 1252.7 487 19th

FAQ

What score does Mixtral 8B get on HellaSwag?

Mixtral 8B scores 71.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mixtral 8B rank on HellaSwag?

It ranks #510 of 600 models, in the 15th percentile. The leader is GPT-5.2 Max at 96.1.

Is Mixtral 8B 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 8B cost?

Mixtral 8B costs $0.91 per million input tokens and $4.38 per million output tokens.

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