Commonsense · Mistral AI

Mistral Large 3 Instruct on HellaSwag: score, rank and what it means

Mistral Large 3 Instruct scores 89.1 on HellaSwag, placing it #110 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
89.1
0–100 scale
Rank
#110
of 600
Percentile
82th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
7.0
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Mistral Large 3 Instruct 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, Mistral Large 3 Instruct sits at #110 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 7.0 points. The median model in this index scores 83.6, which puts Mistral Large 3 Instruct above the midpoint.

Mistral AI models average 79.8 on this benchmark. Mistral Large 3 Instruct is 9.3 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 86.8. Mistral Large 3 Instruct is 2.3 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 89.1 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 $5.31 per million input tokens, Mistral Large 3 Instruct is above 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
Sonar Pro Turbo Perplexity 128000 $13.55 79.0
DeepSeek-V3.2 Chat DeepSeek 1000000 $5.80 82.5
ERNIE 4.5 Baidu 65536 $13.44 80.0
Llama 4 Maverick Base Meta AI 128000 $4.68 79.1
Mistral Large 3 Instruct Mistral AI 400000 $5.31 81.1
Magistral Instruct Mistral AI 65536 $4.48 78.4
Nova Pro Reasoning Amazon 200000 $13.48 79.4

Other benchmarks for Mistral Large 3 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.3 116 81th
GPQA Diamond 79.8 60 90th
SWE-bench Verified 71.9 76 87th
HumanEval 84.2 129 79th
MATH-500 83.4 140 77th
AIME 2025 76.2 137 77th
LiveCodeBench 75.1 94 84th
IFEval 87.6 113 81th
TruthfulQA 85.5 60 90th
MMMU 76.5 125 79th
Arena Elo 1446.2 88 85th

FAQ

What score does Mistral Large 3 Instruct get on HellaSwag?

Mistral Large 3 Instruct scores 89.1 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mistral Large 3 Instruct rank on HellaSwag?

It ranks #110 of 600 models, in the 82nd percentile. The leader is GPT-5.2 Max at 96.1.

Is Mistral Large 3 Instruct good at HellaSwag?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Mistral Large 3 Instruct cost?

Mistral Large 3 Instruct costs $5.31 per million input tokens and $22.47 per million output tokens.

Related