Commonsense · Cohere

Command A Max on HellaSwag: score, rank and what it means

Command A Max scores 87.1 on HellaSwag, placing it #171 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
87.1
0–100 scale
Rank
#171
of 600
Percentile
72th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
9.0
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Command A Max 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, Command A Max sits at #171 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 9.0 points. The median model in this index scores 83.6, which puts Command A Max above the midpoint.

Cohere models average 79.9 on this benchmark. Command A Max is 7.2 points above that provider line, so it is a stronger result than the average Cohere model.

Among multimodal models, the average is 86.8. Command A Max is 0.3 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 87.1 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 $14.28 per million input tokens, Command A Max is above 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
Llama 3.3 Groq Chat Groq 32768 $4.06 76.8
Nova Pro Pro Amazon 200000 $13.03 79.5
Seed-OSS Instruct ByteDance 128000 $3.79 76.0
Claude Opus 4.5 Mini Anthropic 65536 $12.72 79.0
Command A Max Cohere 400000 $14.28 79.9
Grok 4 Mini xAI 65536 $12.21 77.9
Llama 3.3 Chat Meta AI 32768 $4.18 76.9

Other benchmarks for Command A Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.3 73 88th
GPQA Diamond 74.5 153 75th
SWE-bench Verified 69.7 116 81th
HumanEval 83.4 147 76th
MATH-500 85.7 97 84th
AIME 2025 77.2 126 79th
LiveCodeBench 73.1 124 79th
IFEval 86.7 140 77th
TruthfulQA 82.2 125 79th
MMMU 74.6 166 72th
Arena Elo 1443.7 91 85th

FAQ

What score does Command A Max get on HellaSwag?

Command A Max scores 87.1 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Command A Max rank on HellaSwag?

It ranks #171 of 600 models, in the 72nd percentile. The leader is GPT-5.2 Max at 96.1.

Is Command A Max 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 Command A Max cost?

Command A Max costs $14.28 per million input tokens and $70.22 per million output tokens.

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