Reasoning · Cohere

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

Embed 4 Turbo scores 58.4 on GPQA Diamond, placing it #422 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
58.4
0–100 scale
Rank
#422
of 600
Percentile
30th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
28.6
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Embed 4 Turbo 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 Turbo sits at #422 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 28.6 points. The median model in this index scores 68.8, which puts Embed 4 Turbo below the midpoint.

Cohere models average 63.7 on this benchmark. Embed 4 Turbo is 5.3 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 Turbo is 4.5 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 58.4 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 $5.13 per million input tokens, Embed 4 Turbo 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
Llama 4 Scout 8B Meta AI 8192 $1.46 61.2
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
GPT-NeoX Instruct EleutherAI 16384 $1.52 62.6
StableLM 2 Base Stability AI 8192 $1.49 61.9
Embed 4 Turbo Cohere 4096 $5.13 64.0
SmolLM3 Instruct Hugging Face 8192 $1.69 63.6
Pythia Instruct EleutherAI 8192 $1.41 60.8

Other benchmarks for Embed 4 Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 70.6 392 35th
SWE-bench Verified 50.7 415 31th
HumanEval 70.0 392 35th
MATH-500 68.7 391 35th
AIME 2025 53.1 432 28th
LiveCodeBench 55.0 405 33th
IFEval 73.4 411 32th
TruthfulQA 67.6 421 30th
HellaSwag 77.1 415 31th
MMMU 59.5 433 28th
Arena Elo 1324.1 394 34th

FAQ

What score does Embed 4 Turbo get on GPQA Diamond?

Embed 4 Turbo scores 58.4 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Embed 4 Turbo rank on GPQA Diamond?

It ranks #422 of 600 models, in the 30th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Embed 4 Turbo 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 Turbo cost?

Embed 4 Turbo costs $5.13 per million input tokens and $22.04 per million output tokens.

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