Commonsense · Groq

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

Mixtral Groq 1.5B scores 66.3 on HellaSwag, placing it #574 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
66.3
0–100 scale
Rank
#574
of 600
Percentile
4th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
29.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Mixtral Groq 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 Groq 1.5B sits at #574 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 29.8 points. The median model in this index scores 83.6, which puts Mixtral Groq 1.5B below the midpoint.

Groq models average 78.4 on this benchmark. Mixtral Groq 1.5B is 12.1 points below that provider line, so it is a weaker result than the average Groq model.

Among small open-weight models, the average is 70.2. Mixtral Groq 1.5B is 3.9 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 66.3 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 $0.34 per million input tokens, Mixtral Groq 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
Yi-Large 1.5B 01.AI 8192 $0.42 46.8
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Llama 3.3 Groq 1.5B Groq 4096 $0.46 50.0
Llama 3 DeepInfra 1.5B DeepInfra 32768 $0.48 48.8
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
DBRX 1.5B Databricks 16384 $0.32 47.0
SmolLM3 8B Hugging Face 32768 $0.21 44.0

Other benchmarks for Mixtral Groq 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 55.1 571 5th
GPQA Diamond 40.2 585 3th
SWE-bench Verified 28.5 582 3th
HumanEval 49.4 577 4th
MATH-500 44.1 582 3th
AIME 2025 30.9 582 3th
LiveCodeBench 32.8 578 4th
IFEval 59.0 577 4th
TruthfulQA 53.6 581 3th
MMMU 46.8 573 5th
Arena Elo 1172.0 581 3th

FAQ

What score does Mixtral Groq 1.5B get on HellaSwag?

Mixtral Groq 1.5B scores 66.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mixtral Groq 1.5B rank on HellaSwag?

It ranks #574 of 600 models, in the 4th percentile. The leader is GPT-5.2 Max at 96.1.

Is Mixtral Groq 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 Groq 1.5B cost?

Mixtral Groq 1.5B costs $0.34 per million input tokens and $1.24 per million output tokens.

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