Llama 3.3 Groq Instruct on MMMU: score, rank and what it means
Llama 3.3 Groq Instruct scores 73.5 on MMMU, placing it #205 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 Llama 3.3 Groq Instruct 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, Llama 3.3 Groq Instruct sits at #205 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 13.4 points. The median model in this index scores 70.0, which puts Llama 3.3 Groq Instruct above the midpoint.
Groq models average 62.8 on this benchmark. Llama 3.3 Groq Instruct is 10.7 points above that provider line, so it is a stronger result than the average Groq model.
Among multimodal models, the average is 74.3. Llama 3.3 Groq Instruct is 0.8 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 73.5 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 $4.08 per million input tokens, Llama 3.3 Groq Instruct is above 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 |
|---|---|---|---|---|
| o4 Mini | OpenAI | 200000 | $11.92 | 77.7 |
| Kimi K1.5 Chat | Moonshot AI | 128000 | $5.11 | 80.2 |
| GLM-4.6 Chat | Zhipu AI | 400000 | $4.89 | 79.8 |
| Kimi K2 Base | Moonshot AI | 65536 | $4.82 | 79.2 |
| Llama 3.3 Groq Instruct | Groq | 65536 | $4.08 | 76.7 |
| Seed-OSS | ByteDance | 32768 | $3.74 | 75.3 |
| Llama 3.3 Chat | Meta AI | 32768 | $4.18 | 76.9 |
Other benchmarks for Llama 3.3 Groq Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 81.2 | 142 | 76th | |
| GPQA Diamond | 74.0 | 169 | 72th | |
| SWE-bench Verified | 65.1 | 212 | 65th | |
| HumanEval | 79.6 | 246 | 59th | |
| MATH-500 | 79.3 | 227 | 62th | |
| AIME 2025 | 74.7 | 160 | 73th | |
| LiveCodeBench | 66.5 | 265 | 56th | |
| IFEval | 85.7 | 167 | 72th | |
| TruthfulQA | 79.7 | 195 | 68th | |
| HellaSwag | 84.8 | 257 | 57th | |
| Arena Elo | 1394.0 | 234 | 61th |
FAQ
What score does Llama 3.3 Groq Instruct get on MMMU?
Llama 3.3 Groq Instruct scores 73.5 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Llama 3.3 Groq Instruct rank on MMMU?
It ranks #205 of 600 models, in the 66th percentile. The leader is GPT-5.2 Max at 86.9.
Is Llama 3.3 Groq Instruct good at MMMU?
Yes, relative to the index: it is above the median and inside the top half of scores. 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 Llama 3.3 Groq Instruct cost?
Llama 3.3 Groq Instruct costs $4.08 per million input tokens and $22.27 per million output tokens.