Coding · Groq

Mixtral Groq on LiveCodeBench: score, rank and what it means

Mixtral Groq scores 64.1 on LiveCodeBench, placing it #314 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
64.1
0–100 scale
Rank
#314
of 600
Percentile
48th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
21.0
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Mixtral Groq highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Mixtral Groq sits at #314 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 21.0 points. The median model in this index scores 64.7, which puts Mixtral Groq below the midpoint.

Groq models average 55.6 on this benchmark. Mixtral Groq is 8.5 points above that provider line, so it is a stronger result than the average Groq model.

Among open-weight models, the average is 59.1. Mixtral Groq is 5.0 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 64.1 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 $3.37 per million input tokens, Mixtral Groq is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GPT-4.1 Nano OpenAI 32768 $7.42 70.5
GPT-5.2 Nano OpenAI 128000 $9.73 73.5
Grok 3 Mini xAI 200000 $9.67 73.9
Nemotron 4 Base NVIDIA 8192 $3.29 73.0
Mixtral Groq Groq 16384 $3.37 73.1
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
DBRX Databricks 65536 $3.29 73.3

Other benchmarks for Mixtral Groq

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.1 331 45th
GPQA Diamond 66.1 343 43th
SWE-bench Verified 62.0 281 53th
HumanEval 78.7 271 55th
MATH-500 74.9 329 45th
AIME 2025 67.5 303 50th
IFEval 81.2 300 50th
TruthfulQA 78.6 235 61th
HellaSwag 85.0 247 59th
MMMU 70.7 280 53th
Arena Elo 1388.6 254 58th

FAQ

What score does Mixtral Groq get on LiveCodeBench?

Mixtral Groq scores 64.1 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Mixtral Groq rank on LiveCodeBench?

It ranks #314 of 600 models, in the 48th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Mixtral Groq good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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 cost?

Mixtral Groq costs $3.37 per million input tokens and $15.23 per million output tokens.

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