gemini-3-pro-preview
Gemini 3.1 Pro is the next iteration in the Gemini 3 series of models, a suite of highly capable, natively multimodal reasoning models.
text → text · made by Google
Sold by 8 ways
| Seller | Lane | Rate |
|---|---|---|
| Google Vertex AI 0 ways | $1per Mtok in$6per Mtok out | |
| Google Vertex AI cloudnot on the seller's list today | batch | $1per Mtok in$6per Mtok outraw.githubusercontent.com · read 2026-09-22 |
| Databricks cloud | standard | $2per Mtok in$12per Mtok out$0.2per Mtok cached$2.5per Mtok cache writemodels.dev · read 2026-10-31 |
| Google Vertex AI 0 ways | $2per Mtok in$12per Mtok out$0.2per Mtok cached | |
| Google Vertex AI cloudnot on the seller's list today | standard | $2per Mtok in$12per Mtok out$0.2per Mtok cachedraw.githubusercontent.com · read 2026-09-22 |
| Google Vertex AI 0 ways | $3.6per Mtok in$21.6per Mtok out$0.36per Mtok cached | |
| Google Vertex AI cloudnot on the seller's list today | priority | $3.6per Mtok in$21.6per Mtok out$0.36per Mtok cachedraw.githubusercontent.com · read 2026-09-22 |
| Google Vertex AI 0 ways | $4per Mtok in$18per Mtok out$0.4per Mtok cached | |
| Google Vertex AI cloudnot on the seller's list today | long-context | $4per Mtok in$18per Mtok out$0.4per Mtok cachedraw.githubusercontent.com · read 2026-09-22 |
| Requesty 2 ways | $0.9per Mtok in$5.4per Mtok out$0.18per Mtok cached | |
| Requesty aggregatornot on the seller's list today | google flex | $0.9per Mtok in$5.4per Mtok out$0.18per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | $2per Mtok in$12per Mtok out$0.2per Mtok cachedrouter.requesty.ai · read 2026-10-09 | |
| Requesty aggregator | vertex | $2per Mtok in$12per Mtok out$0.2per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
Measured 34 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 1stof 38 | Vpct — Epoch AI | Correct | 0.91 |
| 4thof 18 | Algotune — Epoch AI | Score | 1.83 |
| 4thof 41 | Balrog — Epoch AI | Average progress | 0.581 |
| 5thof 11 | Gdpval — Epoch AI | Win Rate (%) | 0.403 |
| 7thof 102 | Simplebench — Epoch AI | Score (AVG@5) | 0.764 |
| 8thof 46 | Enigma eval — Epoch AI | Accuracy | 18.24 |
| 8thof 56 | Humanity's Last Exam (Epoch AI replication) | Accuracy | 37.52 |
| 9thof 49 | Metr time horizons — Epoch AI | average_score | 0.71 |
| 10thof 34 | LMArena · Search | Score (Elo) | 1207 |
| 13thof 165 | LMArena · Vision | Score (Elo) | 1289 |
| 15thof 92 | Forecastbench — Epoch AI | Overall score | 65.2 |
| 15thof 72 | Frontiermath tier 4 — Epoch AI | mean_score | 18.75 |
| 17thof 23 | Cl bench — Epoch AI | Overall | 0.158 |
| 17thof 101 | FrontierMath (Tiers 1-3) | mean_score | 37.6 |
| 17thof 18 | Rli — Epoch AI | Score | 1.25 |
| 19thof 42 | Gso — Epoch AI | Score OPT@1 | 0.186 |
| 19thof 414 | LMArena · Text | Score (Elo) | 1485 |
| 22ndof 35 | Swe bench verified — Epoch AI | mean_score | 72.934 |
| 27thof 202 | Terminalbench — Epoch AI | Accuracy mean | 0.694 |
| 28thof 41 | Deepresearchbench — Epoch AI | Average score (low) | 0.463 |
| 28thof 326 | GPQA Diamond | mean_score | 92.614 |
| 28thof 71 | Vending bench 2 — Epoch AI | Score | 5478.158 |
| 35thof 173 | Weirdml — Epoch AI | Accuracy | 69.93 |
| 49thof 132 | Ale bench — Epoch AI | Performance | 1176.75 |
| 53rdof 84 | Proofbench — Epoch AI | Accuracy | 20 |
| 72ndof 306 | OTIS Mock AIME 2024-2025 | mean_score | 91.389 |
| 74thof 141 | LMArena · WebDev | Score (Elo) | 1440 |
| 75thof 135 | Webdev arena — Epoch AI | Arena Score | 1438.77 |
| 92ndof 111 | Vectara Hallucination Leaderboard | Hallucination Rate | 13.6 |
| 132ndof 260 | Critpt — Epoch AI | Accuracy | 6.9 |
| 135thof 298 | ARC-AGI-2 (Semi-Private) | Score (%) | 31.11 |
| 141stof 290 | Arc agi 2 — Epoch AI | Score | 31.11 |
| 142ndof 298 | ARC-AGI-1 (Semi-Private) | Score (%) | 75 |
| 150thof 309 | Arc agi — Epoch AI | Score | 75 |
About
gemini-3-pro-preview — a text model from Google, sold by 2 companies from $2 in and $12 out per million tokens, placed 1st of 38 on Vpct — Epoch AI.
It takes text and returns text, with a context window of 1,048,576 tokens. It was published in October 2025, trained on material up to January 2025. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning, code and agents. Two companies sell it. The cheapest is $2 in and $12 out per million tokens at Databricks. Beside the standard rate there is a separately routed lane. It has been measured on 34 boards, and stands best at 1st of 38 on Vpct — Epoch AI.
Every current figure
- Maker
- Register
- model
- Takes
- text
- Returns
- text
- Context
- 1,048,576 tokens
- Longest answer
- 65,536 tokens
- Published
- October 2025
- Knowledge to
- January 2025
- Licence
- not read
- Sellers
- 2
- Maker's own price
- not read
- Price
- $2 in and $12 out per million tokens — Databricks
- Boards
- 34
- Best place
- 1st of 38 — Vpct — Epoch AI
Known as 14 names
Gemini 3 Pro (preview)Gemini-3-Pro-Preview (FC)Gemini-3-Pro-Preview (Prompt)Gemini 3 Pro PreviewGemini 3 Progemini-3-pro-groundinggemini-3-proGemini-3-Pro(11/25)Gemini 3 Pro Preview (2025-11-18)Gemini 3 Pro highlive-SWE-agent + Gemini 3 Pro Preview (2025-11-18)google/gemini-3-pro-previewgoogle/gemini-3-pro-preview:flexvertex/gemini-3-pro-preview