Mathematics · Groq

Mixtral Groq 1.5B on MATH-500: score, rank and what it means

Mixtral Groq 1.5B scores 44.1 on MATH-500, placing it #582 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
44.1
0–100 scale
Rank
#582
of 600
Percentile
3th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
52.6
points

Score distribution

The chart shows the top 10 models on MATH-500, with Mixtral Groq 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Mixtral Groq 1.5B sits at #582 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 52.6 points. The median model in this index scores 76.0, which puts Mixtral Groq 1.5B below the midpoint.

Groq models average 66.1 on this benchmark. Mixtral Groq 1.5B is 22.0 points below that provider line, so it is a weaker result than the average Groq model.

Among small open-weight models, the average is 53.7. Mixtral Groq 1.5B is 9.6 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 44.1 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
StableLM 2 8B Stability AI 32768 $0.38 47.0
SmolLM3 7B Hugging Face 16384 $0.19 44.3
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Mixtral Turbo 1.5B Together AI 4096 $0.31 47.6
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
DBRX 1.5B Databricks 16384 $0.32 47.0
Arctic 1.5B Snowflake 32768 $0.15 43.2

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
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 MATH-500?

Mixtral Groq 1.5B scores 44.1 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Mixtral Groq 1.5B rank on MATH-500?

It ranks #582 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 96.7.

Is Mixtral Groq 1.5B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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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