Gemini 3 Pro vs Mistral Large 2
Direct comparison between google and mistral for chat models. Specs, prices, strengths, weaknesses — decide on facts.
At a glance
- · Cheaper: Gemini 3 Pro
- · Longer context window: Gemini 3 Pro at 2,000,000 tokens
- · Gemini 3 Pro: 2M token context — largest window among top-tier models
- · Mistral Large 2: EU-hosted — GDPR-friendly without US data export
Spec comparison
| Spec | Gemini 3 Pro | Mistral Large 2 |
|---|---|---|
| Provider | mistral | |
| Input per 1M tokens | $1.25 / 1M | $2.00 / 1M |
| Output per 1M tokens | $5.00 / 1M | $6.00 / 1M |
| Context window | 2,000,000 tok | 128,000 tok |
| Max output | 65,536 tok | 8,192 tok |
| Knowledge cutoff | 2025-11 | — |
| Vision | ||
| Audio | ||
| Tool calling | ||
| JSON mode | ||
| Structured output | ||
| Reasoning |
Gemini 3 Pro — strengths
- +2M token context — largest window among top-tier models
- +True multimodal input: video, audio, image, text
- +Very strong on structured output and JSON-schema enforcement
Mistral Large 2 — strengths
- +EU-hosted — GDPR-friendly without US data export
- +Strong on European languages (DE, FR, IT, ES)
- +Solid tool calling and JSON mode
Gemini 3 Pro — weaknesses
- −Code generation slightly behind Claude Sonnet 4.6 and GPT-5.4
- −At very long contexts, latency becomes significant
Mistral Large 2 — weaknesses
- −Code quality behind Sonnet 4.6 and GPT-5.4
- −No native vision