Commonsense · Groq

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

Mixtral Groq scores 85.0 on HellaSwag, placing it #247 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
85.0
0–100 scale
Rank
#247
of 600
Percentile
59th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
11.1
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Mixtral Groq sits at #247 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 11.1 points. The median model in this index scores 83.6, which puts Mixtral Groq above the midpoint.

Groq models average 78.4 on this benchmark. Mixtral Groq is 6.6 points above that provider line, so it is a stronger result than the average Groq model.

Among open-weight models, the average is 80.2. Mixtral Groq is 4.8 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 85.0 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 $3.37 per million input tokens, Mixtral Groq is below the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Hunyuan-Turbo Pro Tencent 65536 $12.00 77.6
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5
Magistral Base Mistral AI 65536 $3.86 75.6
Mistral Small 3 Instruct Mistral AI 32768 $3.97 75.1
Mixtral Groq Groq 16384 $3.37 73.1
Nova Lite Turbo Amazon 8192 $9.14 73.2
Command R+ Chat Cohere 32768 $4.02 76.0

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
LiveCodeBench 64.1 314 48th
IFEval 81.2 300 50th
TruthfulQA 78.6 235 61th
MMMU 70.7 280 53th
Arena Elo 1388.6 254 58th

FAQ

What score does Mixtral Groq get on HellaSwag?

Mixtral Groq scores 85.0 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Mixtral Groq rank on HellaSwag?

It ranks #247 of 600 models, in the 59th percentile. The leader is GPT-5.2 Max at 96.1.

Is Mixtral Groq good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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