Mathematics · Cohere

Embed 4 Mini on MATH-500: score, rank and what it means

Embed 4 Mini scores 54.6 on MATH-500, placing it #523 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
54.6
0–100 scale
Rank
#523
of 600
Percentile
13th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
42.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Embed 4 Mini highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Embed 4 Mini sits at #523 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 42.1 points. The median model in this index scores 76.0, which puts Embed 4 Mini below the midpoint.

Cohere models average 70.8 on this benchmark. Embed 4 Mini is 16.2 points below that provider line, so it is a weaker result than the average Cohere model.

Among mid-range models, the average is 70.0. Embed 4 Mini is 15.4 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 54.6 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 $2.48 per million input tokens, Embed 4 Mini is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 DeepInfra 7B DeepInfra 16384 $0.95 55.6
Llama 3 Hyperbolic 7B Hyperbolic 4096 $0.94 55.6
Llama 4 Scout 1.5B Meta AI 8192 $0.66 53.0
Phi-4 8B Microsoft 32768 $0.96 54.9
Embed 4 Mini Cohere 4096 $2.48 55.8
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
Seed-OSS 7B ByteDance 8192 $0.85 55.5

Other benchmarks for Embed 4 Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.2 486 19th
GPQA Diamond 52.3 496 17th
SWE-bench Verified 43.4 485 19th
HumanEval 60.4 497 17th
AIME 2025 43.9 508 15th
LiveCodeBench 42.9 517 14th
IFEval 67.4 495 18th
TruthfulQA 60.5 524 13th
HellaSwag 73.0 482 20th
MMMU 51.8 533 11th
Arena Elo 1233.2 524 13th

FAQ

What score does Embed 4 Mini get on MATH-500?

Embed 4 Mini scores 54.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Embed 4 Mini rank on MATH-500?

It ranks #523 of 600 models, in the 13th percentile. The leader is GPT-5.2 Max at 96.7.

Is Embed 4 Mini good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 Mini cost?

Embed 4 Mini costs $2.48 per million input tokens and $9.98 per million output tokens.

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