Gemini 3 Flash Turbo on MMLU-Pro: score, rank and what it means
Gemini 3 Flash Turbo scores 87.9 on MMLU-Pro, placing it #18 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with Gemini 3 Flash Turbo highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, Gemini 3 Flash Turbo sits at #18 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 3.7 points. The median model in this index scores 76.1, which puts Gemini 3 Flash Turbo above the midpoint.
Google DeepMind models average 80.4 on this benchmark. Gemini 3 Flash Turbo is 7.5 points above that provider line, so it is a stronger result than the average Google DeepMind model.
Among frontier models, the average is 86.9. Gemini 3 Flash Turbo is 1.0 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 87.9 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 $17.07 per million input tokens, Gemini 3 Flash Turbo is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. 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 |
|---|---|---|---|---|
| Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| Qwen3-Max Reasoning | Alibaba Cloud | 2000000 | $18.12 | 85.9 |
| o4 Turbo | OpenAI | 2000000 | $19.34 | 86.6 |
| Claude Sonnet 4.5 | Anthropic | 400000 | $17.84 | 86.0 |
| Gemini 3 Flash Turbo | Google DeepMind | 200000 | $17.07 | 84.1 |
| Gemini 3 Flash Max | Google DeepMind | 1000000 | $17.43 | 85.0 |
| Grok 4 | xAI | 200000 | $17.90 | 86.5 |
Other benchmarks for Gemini 3 Flash Turbo
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| GPQA Diamond | 77.5 | 96 | 84th | |
| SWE-bench Verified | 72.5 | 68 | 89th | |
| HumanEval | 90.6 | 37 | 94th | |
| MATH-500 | 87.6 | 70 | 88th | |
| AIME 2025 | 81.3 | 69 | 89th | |
| LiveCodeBench | 78.5 | 60 | 90th | |
| IFEval | 88.9 | 85 | 86th | |
| TruthfulQA | 87.4 | 29 | 95th | |
| HellaSwag | 89.5 | 99 | 84th | |
| MMMU | 83.0 | 23 | 96th | |
| Arena Elo | 1473.4 | 27 | 96th |
FAQ
What score does Gemini 3 Flash Turbo get on MMLU-Pro?
Gemini 3 Flash Turbo scores 87.9 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Gemini 3 Flash Turbo rank on MMLU-Pro?
It ranks #18 of 600 models, in the 97th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Gemini 3 Flash Turbo good at MMLU-Pro?
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 MMLU-Pro score calculated?
MMLU-Pro is a knowledge 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 Gemini 3 Flash Turbo cost?
Gemini 3 Flash Turbo costs $17.07 per million input tokens and $69.05 per million output tokens.