Reasoning · Cohere

Embed 4 Nano on GPQA Diamond: score, rank and what it means

Embed 4 Nano scores 45.6 on GPQA Diamond, placing it #560 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
45.6
0–100 scale
Rank
#560
of 600
Percentile
7th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
41.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Embed 4 Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Embed 4 Nano sits at #560 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 41.4 points. The median model in this index scores 68.8, which puts Embed 4 Nano below the midpoint.

Cohere models average 63.7 on this benchmark. Embed 4 Nano is 18.1 points below that provider line, so it is a weaker result than the average Cohere model.

Among mid-range models, the average is 62.9. Embed 4 Nano is 17.3 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 45.6 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 $1.48 per million input tokens, Embed 4 Nano is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Phi-4 1.5B Microsoft 8192 $0.42 48.1
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2
Nemotron 4 1.5B NVIDIA 32768 $0.49 50.8
Embed 4 Nano Cohere 8192 $1.48 49.7
Mixtral 1.5B Mistral AI 16384 $0.36 47.7
Llama 3 Replicate 1.5B Replicate 4096 $0.51 49.3

Other benchmarks for Embed 4 Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 54.5 575 4th
SWE-bench Verified 33.1 571 5th
HumanEval 55.2 540 10th
MATH-500 52.4 537 11th
AIME 2025 33.5 575 4th
LiveCodeBench 40.3 535 11th
IFEval 61.0 564 6th
TruthfulQA 55.6 570 5th
HellaSwag 69.8 537 11th
MMMU 46.2 578 4th
Arena Elo 1207.9 547 9th

FAQ

What score does Embed 4 Nano get on GPQA Diamond?

Embed 4 Nano scores 45.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Embed 4 Nano rank on GPQA Diamond?

It ranks #560 of 600 models, in the 7th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Embed 4 Nano good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Nano cost?

Embed 4 Nano costs $1.48 per million input tokens and $6.14 per million output tokens.

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