Coding · Cohere

Embed 4 Mini on LiveCodeBench: score, rank and what it means

Embed 4 Mini scores 42.9 on LiveCodeBench, placing it #517 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
42.9
0–100 scale
Rank
#517
of 600
Percentile
14th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
42.2
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Embed 4 Mini sits at #517 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 42.2 points. The median model in this index scores 64.7, which puts Embed 4 Mini below the midpoint.

Cohere models average 58.9 on this benchmark. Embed 4 Mini is 16.0 points below that provider line, so it is a weaker result than the average Cohere model.

Among mid-range models, the average is 58.3. 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 42.9 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mistral Large 3 1.5B Mistral AI 32768 $0.82 55.4
Phi-4 7B Microsoft 8192 $0.91 56.8
Mixtral Groq 7B Groq 4096 $0.70 53.4
DeepSeek-R1 1.5B DeepSeek 16384 $1.04 56.6
Embed 4 Mini Cohere 4096 $2.48 55.8
Fusion Nano OpenRouter 8192 $2.96 56.8
Gemma 3 7B Google DeepMind 32768 $0.90 55.9

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
MATH-500 54.6 523 13th
AIME 2025 43.9 508 15th
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 LiveCodeBench?

Embed 4 Mini scores 42.9 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Embed 4 Mini rank on LiveCodeBench?

It ranks #517 of 600 models, in the 14th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Embed 4 Mini good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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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