Knowledge · Cohere

Embed 4 Reasoning on MMLU-Pro: score, rank and what it means

Embed 4 Reasoning scores 70.1 on MMLU-Pro, placing it #395 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
70.1
0–100 scale
Rank
#395
of 600
Percentile
34th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
21.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Embed 4 Reasoning highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Embed 4 Reasoning sits at #395 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 21.5 points. The median model in this index scores 76.1, which puts Embed 4 Reasoning below the midpoint.

Cohere models average 72.3 on this benchmark. Embed 4 Reasoning is 2.2 points below that provider line, so it is a weaker result than the average Cohere model.

Among mid-range models, the average is 71.5. Embed 4 Reasoning is 1.4 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 70.1 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 $5.50 per million input tokens, Embed 4 Reasoning is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nemotron Nano Chat NVIDIA 32768 $2.21 66.2
Embed 4 Turbo Cohere 4096 $5.13 64.0
Nemotron Nano NVIDIA 8192 $2.24 66.6
Doubao 1.5 Pro Nano ByteDance 16384 $5.78 66.6
Embed 4 Reasoning Cohere 4096 $5.50 65.3
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
Command A Nano Cohere 8192 $5.90 66.3

Other benchmarks for Embed 4 Reasoning

BenchmarkScoreRankPercentileRelative
GPQA Diamond 62.8 385 36th
SWE-bench Verified 49.2 427 29th
HumanEval 68.9 409 32th
MATH-500 67.1 406 32th
AIME 2025 57.9 400 33th
LiveCodeBench 56.1 396 34th
IFEval 76.0 389 35th
TruthfulQA 70.4 396 34th
HellaSwag 76.5 420 30th
MMMU 62.8 400 33th
Arena Elo 1310.3 408 32th

FAQ

What score does Embed 4 Reasoning get on MMLU-Pro?

Embed 4 Reasoning scores 70.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Embed 4 Reasoning rank on MMLU-Pro?

It ranks #395 of 600 models, in the 34th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Embed 4 Reasoning good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Reasoning cost?

Embed 4 Reasoning costs $5.50 per million input tokens and $26.10 per million output tokens.

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