Commonsense · Mistral AI

Mixtral 1.5B on HellaSwag: score, rank and what it means

Mixtral 1.5B scores 64.9 on HellaSwag, placing it #585 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
64.9
0–100 scale
Rank
#585
of 600
Percentile
3th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
31.2
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Mixtral 1.5B 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 1.5B sits at #585 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 31.2 points. The median model in this index scores 83.6, which puts Mixtral 1.5B below the midpoint.

Mistral AI models average 79.8 on this benchmark. Mixtral 1.5B is 14.9 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 1.5B is 5.3 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 64.9 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 $0.36 per million input tokens, Mixtral 1.5B 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
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
StableLM 2 7B Stability AI 8192 $0.28 44.3
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
SmolLM3 7B Hugging Face 16384 $0.19 44.3
Mixtral 1.5B Mistral AI 16384 $0.36 47.7
Zephyr 8B Hugging Face 8192 $0.22 43.0
Zephyr 7B Hugging Face 32768 $0.23 42.5

Other benchmarks for Mixtral 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 52.3 584 3th
GPQA Diamond 45.5 561 7th
SWE-bench Verified 30.5 580 3th
HumanEval 51.1 566 6th
MATH-500 47.3 573 5th
AIME 2025 33.8 574 4th
LiveCodeBench 35.9 561 7th
IFEval 61.6 559 7th
TruthfulQA 54.1 577 4th
MMMU 47.6 567 6th
Arena Elo 1188.2 566 6th

FAQ

What score does Mixtral 1.5B get on HellaSwag?

Mixtral 1.5B scores 64.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mixtral 1.5B rank on HellaSwag?

It ranks #585 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 96.1.

Is Mixtral 1.5B 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 1.5B cost?

Mixtral 1.5B costs $0.36 per million input tokens and $1.50 per million output tokens.

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