Multimodal · Cohere

Command R+ Base on MMMU: score, rank and what it means

Command R+ Base scores 69.5 on MMMU, placing it #315 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
69.5
0–100 scale
Rank
#315
of 600
Percentile
48th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
17.4
points

Score distribution

The chart shows the top 10 models on MMMU, with Command R+ Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

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-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, Command R+ Base sits at #315 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 17.4 points. The median model in this index scores 70.0, which puts Command R+ Base below the midpoint.

Cohere models average 65.1 on this benchmark. Command R+ Base is 4.4 points above that provider line, so it is a stronger result than the average Cohere model.

Among open-weight models, the average is 65.1. Command R+ Base is 4.4 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 69.5 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 $3.24 per million input tokens, Command R+ Base is below the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.3 Groq Base Groq 16384 $3.24 73.5
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Reka Core Mini Reka AI 8192 $7.48 70.1
Auto OpenRouter 32768 $7.53 70.2
Command R+ Base Cohere 65536 $3.24 71.6
Gemini 3 Flash Nano Google DeepMind 32768 $7.56 69.4
Llama 3 Modal Chat Modal 65536 $3.55 73.3

Other benchmarks for Command R+ Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 301 50th
GPQA Diamond 66.8 334 44th
SWE-bench Verified 60.7 310 48th
HumanEval 76.6 314 48th
MATH-500 74.9 325 46th
AIME 2025 63.5 362 40th
LiveCodeBench 62.4 344 43th
IFEval 79.2 349 42th
TruthfulQA 73.9 356 41th
HellaSwag 83.7 289 52th
Arena Elo 1375.6 290 52th

FAQ

What score does Command R+ Base get on MMMU?

Command R+ Base scores 69.5 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Command R+ Base rank on MMMU?

It ranks #315 of 600 models, in the 48th percentile. The leader is GPT-5.2 Max at 86.9.

Is Command R+ Base good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 Command R+ Base cost?

Command R+ Base costs $3.24 per million input tokens and $14.70 per million output tokens.

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