Embed 4 Nano on MMMU: score, rank and what it means
Embed 4 Nano scores 46.2 on MMMU, placing it #578 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.
Score distribution
The chart shows the top 10 models on MMMU, with Embed 4 Nano highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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, Embed 4 Nano sits at #578 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 40.7 points. The median model in this index scores 70.0, which puts Embed 4 Nano below the midpoint.
Cohere models average 65.1 on this benchmark. Embed 4 Nano is 18.9 points below that provider line, so it is a weaker result than the average Cohere model.
Among mid-range models, the average is 65.0. Embed 4 Nano is 18.8 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 46.2 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 $1.48 per million input tokens, Embed 4 Nano 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3 Novita 1.5B | Novita AI | 4096 | $0.41 | 49.1 |
| Nemotron Nano 7B | NVIDIA | 8192 | $0.35 | 47.5 |
| Llama 3 DeepInfra 1.5B | DeepInfra | 32768 | $0.48 | 48.8 |
| OLMo 2 1.5B | Allen Institute for AI | 16384 | $0.28 | 44.0 |
| Embed 4 Nano | Cohere | 8192 | $1.48 | 49.7 |
| Nemotron Nano 8B | NVIDIA | 8192 | $0.46 | 48.1 |
| Phi-4 1.5B | Microsoft | 8192 | $0.42 | 48.1 |
Other benchmarks for Embed 4 Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 54.5 | 575 | 4th | |
| GPQA Diamond | 45.6 | 560 | 7th | |
| SWE-bench Verified | 33.1 | 571 | 5th | |
| HumanEval | 55.2 | 540 | 10th | |
| MATH-500 | 52.4 | 537 | 11th | |
| AIME 2025 | 33.5 | 575 | 4th | |
| LiveCodeBench | 40.3 | 535 | 11th | |
| IFEval | 61.0 | 564 | 6th | |
| TruthfulQA | 55.6 | 570 | 5th | |
| HellaSwag | 69.8 | 537 | 11th | |
| Arena Elo | 1207.9 | 547 | 9th |
FAQ
What score does Embed 4 Nano get on MMMU?
Embed 4 Nano scores 46.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Embed 4 Nano rank on MMMU?
It ranks #578 of 600 models, in the 4th percentile. The leader is GPT-5.2 Max at 86.9.
Is Embed 4 Nano 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 Embed 4 Nano cost?
Embed 4 Nano costs $1.48 per million input tokens and $6.14 per million output tokens.