Coding · Groq

Mixtral Groq 7B on LiveCodeBench: score, rank and what it means

Mixtral Groq 7B scores 43.2 on LiveCodeBench, placing it #515 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
43.2
0–100 scale
Rank
#515
of 600
Percentile
14th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
41.9
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Mixtral Groq 7B 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 7B sits at #515 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 41.9 points. The median model in this index scores 64.7, which puts Mixtral Groq 7B below the midpoint.

Groq models average 55.6 on this benchmark. Mixtral Groq 7B is 12.4 points below that provider line, so it is a weaker result than the average Groq model.

Among small open-weight models, the average is 41.2. Mixtral Groq 7B is 2.0 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 43.2 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Command R+ 8B Cohere 8192 $1.21 57.7
GLM-4.5 1.5B Zhipu AI 16384 $0.65 53.3
Mistral Large 3 1.5B Mistral AI 32768 $0.82 55.4
Phi-4 7B Microsoft 8192 $0.91 56.8
Mixtral Groq 7B Groq 4096 $0.70 53.4
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
Embed 4 Mini Cohere 4096 $2.48 55.8

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
MATH-500 51.1 546 9th
AIME 2025 43.2 520 13th
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 LiveCodeBench?

Mixtral Groq 7B scores 43.2 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Mixtral Groq 7B rank on LiveCodeBench?

It ranks #515 of 600 models, in the 14th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Mixtral Groq 7B 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 7B cost?

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

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