Coding · Groq

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

Mixtral Groq Base scores 58.8 on LiveCodeBench, placing it #380 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
58.8
0–100 scale
Rank
#380
of 600
Percentile
37th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
26.3
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Mixtral Groq Base 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 Base sits at #380 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 26.3 points. The median model in this index scores 64.7, which puts Mixtral Groq Base below the midpoint.

Groq models average 55.6 on this benchmark. Mixtral Groq Base is 3.2 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 Base is 0.3 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 58.8 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 $2.66 per million input tokens, Mixtral Groq Base 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
Gemini 2.5 Pro Nano Google DeepMind 32768 $7.28 69.2
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3
Auto OpenRouter 32768 $7.53 70.2
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
Mixtral Groq Base Groq 32768 $2.66 68.4
Reka Core Nano Reka AI 16384 $5.45 65.1
Molmo Chat Allen Institute for AI 32768 $2.40 66.7

Other benchmarks for Mixtral Groq Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.0 389 35th
GPQA Diamond 64.4 374 38th
SWE-bench Verified 54.9 386 36th
HumanEval 71.8 381 37th
MATH-500 70.9 381 37th
AIME 2025 64.5 349 42th
IFEval 76.3 385 36th
TruthfulQA 74.9 332 45th
HellaSwag 81.1 368 39th
MMMU 64.0 390 35th
Arena Elo 1335.6 381 37th

FAQ

What score does Mixtral Groq Base get on LiveCodeBench?

Mixtral Groq Base scores 58.8 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Mixtral Groq Base rank on LiveCodeBench?

It ranks #380 of 600 models, in the 37th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Mixtral Groq Base 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 Base cost?

Mixtral Groq Base costs $2.66 per million input tokens and $11.35 per million output tokens.

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