Gemini 3.1 Pro Preview vs Mistral Large 3 2512
GoogleMistral AIboth via one key, provider price + 3%
Gemini 3.1 Pro Preview and Mistral Large 3 2512 sit at opposite ends of the price-performance curve. Gemini is Google's frontier reasoning model with a 1,048,576-token context window and mandatory reasoning traces; Mistral Large 3 2512 is a 675B-parameter sparse MoE model (41B active) released under Apache 2.0 with a 262,144-token window. The gap in intelligence and coding benchmarks is large, and so is the gap in price — this comparison is about deciding whether that gap is worth paying for.
Spec vs spec
| Spec | Gemini 3.1 Pro Preview | Mistral Large 3 2512 |
|---|---|---|
| Context window | 1.0M | 262K |
| Max output | 66K | — |
| Input modalities | audio, file, image, text, video | text, image, file |
| Output modalities | text | text |
| Released | Feb 19, 2026 | Dec 1, 2025 |
| Reasoning | always on | — |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
google/gemini-3.1-pro-preview
Input · 1M tokens
$2.00 + 3%$2.06
Output · 1M tokens
$12.00 + 3%$12.36
Cache read · 1M tokens
$0.200 + 3%$0.206
Cache write · 1M tokens
$0.375 + 3%$0.386
FEE — FLAT, EVERY MODEL3%
mistralai/mistral-large-2512
Input · 1M tokens
$0.500 + 3%$0.515
Output · 1M tokens
$1.50 + 3%$1.54
Cache read · 1M tokens
$0.050 + 3%$0.052
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
google/gemini-3.1-pro-preview
$45.32
$44.00 provider + 3%
mistralai/mistral-large-2512Cheaper
$8.24
$8.00 provider + 3%
Benchmarks
Design Arena categories where both models have results. Higher Elo and lower rank win.
| Gemini 3.1 Pro Preview | Mistral Large 3 2512 | |||
|---|---|---|---|---|
| Category | Elo | Rank | Elo | Rank |
| 3D | 1303 | #17 | 1176 | #51 |
| ASCII art | 1314 | #4 | 1115 | #43 |
| Code | 1290 | #18 | 1191 | #56 |
| Data viz | 1270 | #20 | 1180 | #55 |
| Game dev | 1264 | #26 | 1146 | #65 |
| SVG | 1347 | #2 | 1050 | #62 |
| UI components | 1322 | #8 | 1157 | #59 |
| Websites | 1294 | #15 | 1205 | #53 |
Head-to-head preference voting. How we filter and rank
Pricing math
Gemini 3.1 Pro Preview costs $2.00/$12.00 per million tokens (prompt/completion) from Google; on OpenKey that's $2.06/$12.36 after the flat 3% fee ($2.00 × 1.03, $12.00 × 1.03). Mistral Large 3 2512 costs $0.50/$1.50 provider-side, or $0.515/$1.545 on OpenKey. Run a 10M-input/2M-output workload and Gemini costs $44.00 versus Mistral's $8.00 — a 5.5x difference. Gemini's input price alone is 4x Mistral's ($2.00 vs $0.50), which is also the exact ratio of their context windows (1,048,576 vs 262,144, a 4.0x context ratio). If you're processing high token volumes with routine requests, that multiplier compounds fast.
Coding and agentic performance
On Artificial Analysis benchmarks, Gemini 3.1 Pro Preview scores 68.8 on the coding index against Mistral's 20.1, and 21.4 on the agentic index against Mistral's 5.5. On Design Arena's agentic categories — fullstack (elo 1139, rank 16), webapps (elo 1196, rank 13), and htmlslides (elo 1209, rank 6) — Gemini has data points Mistral doesn't even compete in, since Mistral's Design Arena results are limited to the non-agentic 'models' arena. Where Mistral does show up, like codecategories (elo 1191, rank 56) and website (elo 1205, rank 53), it trails Gemini's equivalents (codecategories elo 1290 rank 18; website elo 1294 rank 15) by a wide margin.
Context and long-document work
Gemini's 1,048,576-token context window is 4x Mistral Large 3 2512's 262,144 tokens. For anything involving large codebases, long transcripts, or multi-document retrieval without chunking, Gemini has more headroom. Gemini also supports higher max completion output at 65,536 tokens; Mistral's max completion tokens field isn't specified in its listing. If your workload needs to hold an entire repo or a long research corpus in context at once, Mistral's smaller window may force you into retrieval or chunking strategies Gemini doesn't need.
Modality and tooling differences
Gemini 3.1 Pro Preview accepts text, image, file, audio, and video input — Mistral Large 3 2512 accepts text, image, and file only, with no audio or video. Both output text only. Gemini also exposes reasoning controls (`reasoning`, `include_reasoning`, three effort levels: low/medium/high, defaulting to medium) that Mistral's parameter list doesn't include. Mistral's parameter set instead includes `frequency_penalty` and `presence_penalty`, which Gemini's list omits. If your pipeline needs audio/video ingestion or explicit reasoning-effort tuning, Gemini is the only one of the two that supports it.
When to pick each
Pick Gemini 3.1 Pro Preview when the task is complex agentic coding, multimodal input, or requires the largest context window you can get — the intelligence index gap (46.5 vs 15.9) is too large to ignore for hard reasoning work. Pick Mistral Large 3 2512 when you're running high-volume, cost-sensitive workloads, want an Apache 2.0 licensed model you can self-host or audit, or don't need audio/video input. Both models run on OpenKey under one API key with the same flat 3% fee on provider pricing, so switching between them for different jobs doesn't add integration overhead.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| Agentic coding / fullstack app generation | Gemini 3.1 Pro Preview | Agentic index of 21.4 vs Mistral's 5.5, plus fullstack elo 1139 (rank 16) on Design Arena |
| High-volume batch processing on a budget | Mistral Large 3 2512 | $8.00 vs $44.00 on a 10M-in/2M-out workload — 5.5x cheaper |
| Long-document or large-codebase analysis | Gemini 3.1 Pro Preview | 1,048,576-token context is 4x Mistral's 262,144 |
| Open-weight / self-hostable deployments | Mistral Large 3 2512 | Apache 2.0 license, 675B total params with 41B active in a sparse MoE |
| Audio or video input pipelines | Gemini 3.1 Pro Preview | Only model of the two that accepts audio and video input modalities |
| SVG or UI component generation | Gemini 3.1 Pro Preview | SVG elo 1347 (rank 2) and uicomponent elo 1322 (rank 8) vs Mistral's SVG elo 1050 (rank 62) |
Questions
- How much more expensive is Gemini 3.1 Pro Preview than Mistral Large 3 2512?
- On a 10M-input/2M-output workload, Gemini costs $44.00 versus Mistral's $8.00 — a 5.5x difference. The input price ratio alone is 4.0x ($2.00 vs $0.50 per million tokens provider-side), matching the models' 4.0x context-window ratio.
- Which model has the bigger context window?
- Gemini 3.1 Pro Preview supports 1,048,576 tokens of context, 4x Mistral Large 3 2512's 262,144 tokens. That matters for large codebases or long documents you don't want to chunk.
- Is Mistral Large 3 2512 open source?
- Yes. It's released under the Apache 2.0 license, with a sparse mixture-of-experts architecture totaling 675B parameters and 41B active parameters per forward pass.
- Which model scores better on coding benchmarks?
- Gemini 3.1 Pro Preview scores 68.8 on the Artificial Analysis coding index versus Mistral Large 3 2512's 20.1 — more than 3x higher. Gemini also outranks Mistral on every Design Arena 'models' category they share, like codecategories (rank 18 vs rank 56).