Knowledge · Groq

Mixtral Groq 1.5B on MMLU-Pro: score, rank and what it means

Mixtral Groq 1.5B scores 55.1 on MMLU-Pro, placing it #571 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
55.1
0–100 scale
Rank
#571
of 600
Percentile
5th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
36.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Mixtral Groq 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Mixtral Groq 1.5B sits at #571 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 36.5 points. The median model in this index scores 76.1, which puts Mixtral Groq 1.5B below the midpoint.

Groq models average 68.9 on this benchmark. Mixtral Groq 1.5B is 13.8 points below that provider line, so it is a weaker result than the average Groq model.

Among small open-weight models, the average is 59.8. Mixtral Groq 1.5B is 4.7 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 55.1 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 $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 MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Anyscale 1.5B Anyscale 16384 $0.43 48.9
Llama 3 Replicate 1.5B Replicate 4096 $0.51 49.3
Molmo 8B Allen Institute for AI 32768 $0.44 49.9
Llama 3.3 Groq 1.5B Groq 4096 $0.46 50.0
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
Mixtral Turbo 1.5B Together AI 4096 $0.31 47.6
Phi-4 1.5B Microsoft 8192 $0.42 48.1

Other benchmarks for Mixtral Groq 1.5B

BenchmarkScoreRankPercentileRelative
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
HellaSwag 66.3 574 4th
MMMU 46.8 573 5th
Arena Elo 1172.0 581 3th

FAQ

What score does Mixtral Groq 1.5B get on MMLU-Pro?

Mixtral Groq 1.5B scores 55.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Mixtral Groq 1.5B rank on MMLU-Pro?

It ranks #571 of 600 models, in the 5th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Mixtral Groq 1.5B good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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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