Knowledge · Cohere

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

Embed 4 Turbo scores 70.6 on MMLU-Pro, placing it #392 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
70.6
0–100 scale
Rank
#392
of 600
Percentile
35th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
21.0
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Embed 4 Turbo 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 Turbo sits at #392 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 21.0 points. The median model in this index scores 76.1, which puts Embed 4 Turbo below the midpoint.

Cohere models average 72.3 on this benchmark. Embed 4 Turbo is 1.7 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 Turbo is 0.9 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 70.6 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 $5.13 per million input tokens, Embed 4 Turbo 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
Sonar Mini Perplexity 65536 $6.52 67.9
Mixtral Groq Base Groq 32768 $2.66 68.4
Mixtral Turbo Base Together AI 32768 $2.53 69.7
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

Other benchmarks for Embed 4 Turbo

BenchmarkScoreRankPercentileRelative
GPQA Diamond 58.4 422 30th
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 MMLU-Pro?

Embed 4 Turbo scores 70.6 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Embed 4 Turbo rank on MMLU-Pro?

It ranks #392 of 600 models, in the 35th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Embed 4 Turbo 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 Turbo cost?

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

Related