Coding · Cohere

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

Embed 4 Max scores 58.2 on LiveCodeBench, placing it #386 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
58.2
0–100 scale
Rank
#386
of 600
Percentile
36th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
26.9
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Embed 4 Max 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 Max sits at #386 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 26.9 points. The median model in this index scores 64.7, which puts Embed 4 Max below the midpoint.

Cohere models average 58.9 on this benchmark. Embed 4 Max is 0.7 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 Max is 0.1 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 58.2 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 $5.68 per million input tokens, Embed 4 Max is above 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
Molmo Chat Allen Institute for AI 32768 $2.40 66.7
Nova Pro Nano Amazon 8192 $5.44 65.4
DBRX Base Databricks 32768 $2.63 69.1
Nemotron Nano NVIDIA 8192 $2.24 66.6
Embed 4 Max Cohere 8192 $5.68 66.1
Reka Flash Mini Reka AI 16384 $5.77 65.5
Sonar Pro Nano Perplexity 32768 $5.50 66.1

Other benchmarks for Embed 4 Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.5 375 38th
GPQA Diamond 59.0 415 31th
SWE-bench Verified 55.1 383 36th
HumanEval 69.6 401 33th
MATH-500 64.8 420 30th
AIME 2025 61.5 377 37th
IFEval 75.3 395 34th
TruthfulQA 68.3 411 32th
HellaSwag 76.9 417 31th
MMMU 66.1 370 38th
Arena Elo 1326.3 392 35th

FAQ

What score does Embed 4 Max get on LiveCodeBench?

Embed 4 Max scores 58.2 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Embed 4 Max rank on LiveCodeBench?

It ranks #386 of 600 models, in the 36th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Embed 4 Max 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 Max cost?

Embed 4 Max costs $5.68 per million input tokens and $21.60 per million output tokens.

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