Commonsense · Cohere

Embed 4 Mini on HellaSwag: score, rank and what it means

Embed 4 Mini scores 73.0 on HellaSwag, placing it #482 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
73.0
0–100 scale
Rank
#482
of 600
Percentile
20th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
23.1
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Embed 4 Mini 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, Embed 4 Mini sits at #482 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 23.1 points. The median model in this index scores 83.6, which puts Embed 4 Mini below the midpoint.

Cohere models average 79.9 on this benchmark. Embed 4 Mini is 6.9 points below that provider line, so it is a weaker result than the average Cohere model.

Among mid-range models, the average is 79.8. Embed 4 Mini is 6.8 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 73.0 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 $2.48 per million input tokens, Embed 4 Mini 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
Magistral 7B Mistral AI 32768 $1.22 58.9
Nemotron 4 7B NVIDIA 16384 $1.05 56.9
Zephyr Base Hugging Face 4096 $1.26 59.5
DeepSeek-Coder 8B DeepSeek 32768 $1.26 58.7
Embed 4 Mini Cohere 4096 $2.48 55.8
QwQ 8B Alibaba Cloud 16384 $1.37 59.5
Qwen3-Coder 7B Alibaba Cloud 32768 $1.24 59.6

Other benchmarks for Embed 4 Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.2 486 19th
GPQA Diamond 52.3 496 17th
SWE-bench Verified 43.4 485 19th
HumanEval 60.4 497 17th
MATH-500 54.6 523 13th
AIME 2025 43.9 508 15th
LiveCodeBench 42.9 517 14th
IFEval 67.4 495 18th
TruthfulQA 60.5 524 13th
MMMU 51.8 533 11th
Arena Elo 1233.2 524 13th

FAQ

What score does Embed 4 Mini get on HellaSwag?

Embed 4 Mini scores 73.0 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Embed 4 Mini rank on HellaSwag?

It ranks #482 of 600 models, in the 20th percentile. The leader is GPT-5.2 Max at 96.1.

Is Embed 4 Mini good at HellaSwag?

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 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 Embed 4 Mini cost?

Embed 4 Mini costs $2.48 per million input tokens and $9.98 per million output tokens.

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