Mathematics · Groq

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

Mixtral Groq Instruct scores 77.0 on MATH-500, placing it #280 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
77.0
0–100 scale
Rank
#280
of 600
Percentile
53th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
19.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with Mixtral Groq Instruct 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 Instruct sits at #280 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 19.7 points. The median model in this index scores 76.0, which puts Mixtral Groq Instruct above the midpoint.

Groq models average 66.1 on this benchmark. Mixtral Groq Instruct is 10.9 points above that provider line, so it is a stronger result than the average Groq model.

Among open-weight models, the average is 70.8. Mixtral Groq Instruct is 6.2 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 77.0 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 $3.25 per million input tokens, Mixtral Groq Instruct 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
Llama 3 Anyscale Base Anyscale 65536 $3.23 72.9
Llama 3.1 Base Meta AI 32768 $3.39 72.2
Llama 3.1 Instruct Meta AI 200000 $4.05 75.7
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Mixtral Groq Instruct Groq 16384 $3.25 72.5
Reka Flash Reasoning Reka AI 32768 $10.70 75.6
Yi-Lightning Base 01.AI 16384 $3.31 72.7

Other benchmarks for Mixtral Groq Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 73.9 356 41th
GPQA Diamond 65.7 346 42th
SWE-bench Verified 57.8 359 40th
HumanEval 74.7 347 42th
AIME 2025 70.6 245 59th
LiveCodeBench 66.2 270 55th
IFEval 80.2 329 45th
TruthfulQA 74.5 341 43th
HellaSwag 85.1 240 60th
MMMU 71.6 252 58th
Arena Elo 1372.7 308 49th

FAQ

What score does Mixtral Groq Instruct get on MATH-500?

Mixtral Groq Instruct scores 77.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Mixtral Groq Instruct rank on MATH-500?

It ranks #280 of 600 models, in the 53rd percentile. The leader is GPT-5.2 Max at 96.7.

Is Mixtral Groq Instruct good at MATH-500?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Instruct cost?

Mixtral Groq Instruct costs $3.25 per million input tokens and $16.01 per million output tokens.

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