Reasoning · Cohere

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

Embed 4 Max scores 59.0 on GPQA Diamond, placing it #415 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
59.0
0–100 scale
Rank
#415
of 600
Percentile
31th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
28.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Embed 4 Max 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 Max sits at #415 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 28.0 points. The median model in this index scores 68.8, which puts Embed 4 Max below the midpoint.

Cohere models average 63.7 on this benchmark. Embed 4 Max is 4.7 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 Max is 3.9 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 59.0 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 $5.68 per million input tokens, Embed 4 Max is above 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
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Kimi K1.5 8B Moonshot AI 8192 $1.54 62.2
Llama 4 Maverick 7B Meta AI 4096 $1.52 61.9
Embed 4 Max Cohere 8192 $5.68 66.1
Firefunction Mini Fireworks AI 32768 $4.63 63.2
Reka Flash Nano Reka AI 16384 $3.93 61.0

Other benchmarks for Embed 4 Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.5 375 38th
SWE-bench Verified 55.1 383 36th
HumanEval 69.6 401 33th
MATH-500 64.8 420 30th
AIME 2025 61.5 377 37th
LiveCodeBench 58.2 386 36th
IFEval 75.3 395 34th
TruthfulQA 68.3 411 32th
HellaSwag 76.9 417 31th
MMMU 66.1 370 38th
Arena Elo 1326.3 392 35th

FAQ

What score does Embed 4 Max get on GPQA Diamond?

Embed 4 Max scores 59.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Embed 4 Max rank on GPQA Diamond?

It ranks #415 of 600 models, in the 31st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Embed 4 Max 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 Max cost?

Embed 4 Max costs $5.68 per million input tokens and $21.60 per million output tokens.

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