Model comparison
Gemini 3.1 Pro vs Mistral Medium 3.5
Google against Mistral, compared on context, price, and verified benchmark results.
Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Gemini 3.1 Pro
Frontier
Mistral
Mistral Medium 3.5
Frontier · Open weights
| Specification | Gemini 3.1 Pro | Mistral Medium 3.5 |
|---|---|---|
| Provider | ||
| Provider | Mistral | |
| Tier | ||
| Tier | Frontier | Frontier |
| Context window | ||
| Context window | Winner: 1.05M | 262K |
| Max output | ||
| Max output | 66K | Not verifiedUnverified |
| Input / 1M tokens | ||
| Input / 1M tokens | $2 | Winner: $1.50 |
| Output / 1M tokens | ||
| Output / 1M tokens | $12 | Winner: $7.50 |
| Weights | ||
| Weights | Closed | Open |
| Parameters | ||
| Parameters | Not disclosedUnverified | 128B dense |
| Reasoning levels | ||
| Reasoning levels | low, medium, high | Not verifiedUnverified |
| Modalities | ||
| Modalities | text, image, video, audio, pdf | text, image |
| License | ||
| License | Not disclosedUnverified | Modified MIT |
| API model id | ||
| API model id | gemini-3.1-pro-preview | mistral-medium-3-5 |
| Released | ||
| Released | February 19, 2026 | April 28, 2026 |
| Artificial Analysis Intelligence Index (2026-09-26) | ||
| Artificial Analysis Intelligence Index (2026-09-26) | Winner: 29.7 | 14.2 |
| SWE-bench Verified (2026-02) | ||
| SWE-bench Verified (2026-02) | 80.6 | Not verifiedUnverified |
| GPQA Diamond (2026-02) | ||
| GPQA Diamond (2026-02) | 94.3 | Not verifiedUnverified |
| Humanity's Last Exam (2026-02) | ||
| Humanity's Last Exam (2026-02) | 44.4 | Not verifiedUnverified |
| Terminal-Bench 2.1 (2026-07) | ||
| Terminal-Bench 2.1 (2026-07) | 73.8 | Not verifiedUnverified |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
Where each score comes from, and how far it can be compared across models.
- 2026-09-26Artificial Analysis
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.
- 2026-07Google DeepMind model evaluation report (vendor, Terminus-2; own Feb report separately reported TB 2.0 = 68.5 — versions preserved)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.
- 2026-02Google DeepMind model evaluation report (vendor, no tools; 51.4 with search+code)
Real GitHub issue resolution: does the model's patch pass the hidden tests.
Comparable with caveatPost-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
Pricing tiers
Gemini 3.1 Pro: $2/$12 per MTok (≤200K); $4/$18 (>200K). Still 'Preview' as of 2026-09-26; no Gemini 3.5 Pro or Gemini 4 release yet.
Mistral Medium 3.5: Mistral first-party API $1.50/$7.50 per MTok; Mistral advertises up to 90% off cached input (exact cached rate not verified). Open weights under a Modified MIT licence. 128B dense.
Gemini 3.1 Pro
Gemini 3.1 Pro is Google's only Pro model (still in Preview), with a 1M-token context and strong multimodal reasoning.
Best for
- Very long documents
- Multimodal reasoning
- Frontier knowledge work
Watch out
Still in Preview; Google says Gemini 4 is in post-training but unreleased as of 2026-09-26, and newer Flash models outscore it on the Artificial Analysis index.
Mistral Medium 3.5
Mistral Medium 3.5 is the model Mistral calls its new flagship — a 128B dense open-weight model with a 256K context, powering its Vibe remote agents.
Best for
- EU-hosted frontier work
- Open-weight self-hosting
- Mistral Vibe agents
Watch out
Far behind US and Chinese frontier models on the Artificial Analysis index; max output is not published. Check the Modified MIT terms before redistribution.
When the cheaper one wins
Mistral Medium 3.5 is cheaper on output at $7.50 per million tokens against $12 for Gemini 3.1 Pro — about 1.6×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 2/5 core specs verified on both sides — Not published for at least one side: max output, parameter count, reasoning levels.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 2 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- Gemini 3.1 Pro: Google Cloud — Gemini 3.1 Pro (accessed 2026-08-29)
- Gemini 3.1 Pro: TechCrunch — Gemini 3.1 Pro (accessed 2026-08-29)
- Mistral Medium 3.5: Mistral docs — Mistral Medium 3.5 (26.04) (accessed 2026-09-26)
- Mistral Medium 3.5: Mistral — Vibe remote agents and Mistral Medium 3.5 (accessed 2026-09-26)
- Mistral Medium 3.5: Mistral changelog (2026-04-28) (accessed 2026-09-26)
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Diving deeper on one model? Gemini 3.1 Pro · Mistral Medium 3.5
Common questions
Gemini 3.1 Pro vs Mistral Medium 3.5
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.1 Pro or Mistral Medium 3.5 cheaper for input?
Is Gemini 3.1 Pro or Mistral Medium 3.5 cheaper for output?
Which has the larger context window, Gemini 3.1 Pro or Mistral Medium 3.5?
Should I use Gemini 3.1 Pro or Mistral Medium 3.5?
Can I self-host Gemini 3.1 Pro or Mistral Medium 3.5?
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Mistral Medium 3.5 costs $1.50 per 1M tokens versus $2 for Gemini 3.1 Pro — a 1.3x difference at the headline tier.
- Context: Gemini 3.1 Pro takes 1.05M against 262K for Mistral Medium 3.5 — only decisive if your prompts approach the smaller window.
- Measured capability: Gemini 3.1 Pro leads Artificial Analysis Intelligence Index 29.7 to 14.2 (measured 2026-09-26).
- Deployment: Mistral Medium 3.5 publishes weights you can self-host; the other is API-only.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.