Gemma 3 vs Mistral Large
Pricing, benchmarks, and use case comparison
Quick take
- •Gemma 3 is meaningfully stronger at cost efficiency (90 vs 66 on our capability index).
- •Mistral Large is meaningfully stronger at reasoning (85 vs 64).
- •Gemma 3 is open-weights (free to self-host); Mistral Large is paid API only.
Specs comparison
| Gemma 3 | Mistral Large | |
|---|---|---|
| Provider | Google DeepMind | Mistral AI |
| Type | Open source | Closed source |
| Context window | 128K tokens (32K for the 1B variant) | 128000 |
| Input / 1M tokens | ✓Free (self-host) | 2.00 |
| Output / 1M tokens | Free (self-host) | 6.00 |
| Release date | 2025-03 | 2024-02 |
Benchmarks
| Benchmark | Gemma 3 | Mistral Large |
|---|---|---|
| MATH (27B) | 89% | - |
| MMMU (27B, multimodal) | 64.9% | - |
| MMLU | - | 84.0% |
| HumanEval | - | 92.0% |
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 Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty