Mathematics · Groq

Mixtral Groq 7B on MATH-500: score, rank and what it means

Mixtral Groq 7B scores 51.1 on MATH-500, placing it #546 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
51.1
0–100 scale
Rank
#546
of 600
Percentile
9th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
45.6
points

Score distribution

The chart shows the top 10 models on MATH-500, with Mixtral Groq 7B 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 7B sits at #546 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 45.6 points. The median model in this index scores 76.0, which puts Mixtral Groq 7B below the midpoint.

Groq models average 66.1 on this benchmark. Mixtral Groq 7B is 15.0 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 7B is 2.6 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 51.1 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 $0.70 per million input tokens, Mixtral Groq 7B 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
Arctic 7B Snowflake 8192 $0.49 50.3
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2
Phi-3.5 7B Microsoft 4096 $0.50 50.5
Mixtral 7B Mistral AI 16384 $0.70 54.1
Mixtral Groq 7B Groq 4096 $0.70 53.4
Llama 3 Replicate 1.5B Replicate 4096 $0.51 49.3
OLMo 2 8B Allen Institute for AI 4096 $0.64 52.5

Other benchmarks for Mixtral Groq 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.3 532 11th
GPQA Diamond 47.5 544 9th
SWE-bench Verified 36.6 545 9th
HumanEval 58.5 519 14th
AIME 2025 43.2 520 13th
LiveCodeBench 43.2 515 14th
IFEval 65.7 525 13th
TruthfulQA 60.1 529 12th
HellaSwag 71.8 504 16th
MMMU 50.2 551 8th
Arena Elo 1227.8 529 12th

FAQ

What score does Mixtral Groq 7B get on MATH-500?

Mixtral Groq 7B scores 51.1 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Mixtral Groq 7B rank on MATH-500?

It ranks #546 of 600 models, in the 9th percentile. The leader is GPT-5.2 Max at 96.7.

Is Mixtral Groq 7B 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 7B cost?

Mixtral Groq 7B costs $0.70 per million input tokens and $2.47 per million output tokens.

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