Gemma 3 vs o1
Pricing, benchmarks, and use case comparison
Quick take
- •Gemma 3 is meaningfully stronger at cost efficiency (90 vs 35 on our capability index).
- •o1 is meaningfully stronger at reasoning (90 vs 64).
- •Gemma 3 is open-weights (free to self-host); o1 is paid API only.
- •Gemma 3 has a 128K tokens (32K for the 1B variant) context window vs 200,000 tokens (100,000 max output) - better for whole-repo or long-document work.
Specs comparison
| Gemma 3 | o1 | |
|---|---|---|
| Provider | Google DeepMind | OpenAI |
| Type | Open source | Closed source |
| Context window | ✓128K tokens (32K for the 1B variant) | 200,000 tokens (100,000 max output) |
| Input / 1M tokens | ✓Free (self-host) | $15.00 |
| Output / 1M tokens | Free (self-host) | $60.00 |
| Release date | 2025-03 | 2024-12 |
Benchmarks
| Benchmark | Gemma 3 | o1 |
|---|---|---|
| MATH (27B) | 89% | - |
| MMMU (27B, multimodal) | 64.9% | - |
| AIME 2024 | - | 74% |
| GPQA Diamond | - | 77.3% |
| Codeforces | - | ~89th percentile |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose Gemma 3 if...
- →You need an open, self-hostable model with a size to match your hardware
- →Multilingual or multimodal tasks on-prem
- →Privacy-sensitive or offline deployments
- →Fine-tuning on your own data
Choose o1 if...
- →Hard, multi-step math, science, and logic problems that reward deliberate reasoning
- →Competitive programming and algorithmic problem solving
- →Existing o1-based pipelines already validated for reasoning tasks