Gemini 3.1 Pro Preview

Reasoning-first Gemini preview for agentic coding and complex problem solving
- Context
- 1.0M
- Released
- 7mo ago
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $12.00
- Cached input / 1M tokens
- $0.20
- Cache write / 1M tokens
- $0.38
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
DeepSWE 1.1
Primary coding-agent benchmark · 113 tasks · Data generated 2026-09-22
- pass@4
- 28.3%
- Average cost / attempt
- $2.14
- Benchmark runs
- 4
pass@1 is the success rate across scored attempts; pass@4 is the share of tasks solved in at least one of four attempts. Costs are reported by DeepSWE for each configuration. These results are not directly comparable to evaluations using different harnesses. Official source JSON.
Other published benchmarks
| Evaluation | Reported score and source |
|---|---|
| ARC-AGI-2 | 77.1% Third-party evaluator · gemini-3.1-pro-preview External evaluation via Epoch AIOriginal-source terms apply |
| FrontierMath-2025-02-28-Private | |
| FrontierMath-Tier-4-2025-07-01-Private | |
| FrontierMath-Tier-4-v2-Private | |
| FrontierMath-Tiers-1-3-v2-Private | |
| GPQA diamond | |
| GPQA diamond | |
| OTIS Mock AIME 2024-2025 | |
| OTIS Mock AIME 2024-2025 | |
| SimpleQA Verified | |
| Terminal Bench | 78.4% Terminal-Bench v2 Leaderboard · gemini-3.1-pro-preview Agent: Forge Code Terminal-Bench v2 LeaderboardOriginal-source terms apply |
| Terminal Bench | 78.4% https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gemini-3.1-pro-preview Agent: ForgeCode https://www.tbench.ai/leaderboard/terminal-bench/2.0Original-source terms apply |
| Terminal Bench | 61.4% https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gemini-3.1-pro-preview Agent: Gemini CLI https://www.tbench.ai/leaderboard/terminal-bench/2.0Original-source terms apply |
| Terminal Bench | 74.8% https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gemini-3.1-pro-preview Agent: Terminus-KIRA https://www.tbench.ai/leaderboard/terminal-bench/2.0Original-source terms apply |
| Terminal Bench | 80.2% https://www.tbench.ai/leaderboard/terminal-bench/2.0 · gemini-3.1-pro-preview Agent: TongAgents https://www.tbench.ai/leaderboard/terminal-bench/2.0Original-source terms apply |
Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.
Specifications
- Developer
- Google DeepMind
- Model family
- Gemini
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- February 19, 2026
- Model ID
google/gemini-3.1-pro-preview- Openness
- Closed
- License
- —
- Input modalities
- audio, file, image, text, video
- Output modalities
- text
- Modality
- text+image+file+audio+video->text
- Tokenizer
- Gemini
- Max output tokens
- 66K
- Knowledge cutoff
- 2025-01
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- google/gemini-3.1-pro-preview
- Source family
- gemini-pro
- Last updated
- 2026-02-19
- Knowledge cutoff
- 2025-01
- Model context
- 1.0M
- Model output limit
- 66K
- Open weights
- No
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Structured output
- Yes
- Temperature control
- Yes
Published benchmarks
| Benchmark | Score | Evaluation details | Evidence |
|---|---|---|---|
| SWE-Bench Pro | 54.2 · resolve rate | 2026-05-28 | Source |
| Terminal-Bench | 70.3 · success rate | Terminus-2 · 2.1 · 2026-05-28 | Source |
| SWE-Bench Pro | 46.1 · resolve rate | public | Source |
| SWE-Atlas Codebase QnA | 13.5 · score | Mini-SWE-Agent | Source |
| SWE-Atlas Refactoring | 33.81 · score | Gemini CLI | Source |
| SWE-Atlas Test Writing | 29.84 · score | Mini-SWE-Agent | Source |
| Artificial Analysis Coding Agent Index | 43 · average pass@1 | Gemini CLI · high | Source |
| SWE-Atlas Codebase QnA | 45.6 · pass@1 | Gemini CLI · high | Source |
| SWE-Bench Pro | 15.1 · pass@1 | Gemini CLI · hard-aa · high | Source |
| Terminal-Bench | 68.3 · pass@1 | Gemini CLI · high · 2.1 | Source |
| GPQA Diamond | 94.3 · accuracy | 2026-04-23 | Source |
| Humanity's Last Exam | 44.4 · accuracy | full set, text + MM · 2026-05-19 | Source |
| ARC-AGI-2 | 77.1 · accuracy | 2026-05-19 | Source |
| MMMU Pro | 80.5 · accuracy | no tools · 2026-05-19 | Source |
| MCP Atlas | 78.2 · success rate | 2026-05-19 | Source |
| OSWorld-Verified | 76.2 · success rate | 2026-05-19 | Source |
| CharXiv Reasoning | 83.3 · accuracy | no tools · 2026-05-19 | Source |
| GDPval-AA | 1314 · Elo | 2026-05-19 | Source |
Complete source record (JSON)
{
"id": "google/gemini-3.1-pro-preview",
"name": "Gemini 3.1 Pro Preview",
"description": "Reasoning-first Gemini preview for agentic coding and complex problem solving",
"family": "gemini-pro",
"last_updated": "2026-02-19",
"knowledge": "2025-01",
"attachment": true,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"video",
"audio",
"pdf"
],
"output": [
"text"
]
},
"limit": {
"context": 1048576,
"output": 65536
},
"benchmarks": [
{
"name": "SWE-Bench Pro",
"score": 54.2,
"source": "https://www.anthropic.com/news/claude-opus-4-8",
"metric": "resolve rate",
"date": "2026-05-28"
},
{
"name": "Terminal-Bench",
"score": 70.3,
"source": "https://www.anthropic.com/news/claude-opus-4-8",
"metric": "success rate",
"harness": "Terminus-2",
"version": "2.1",
"date": "2026-05-28"
},
{
"name": "SWE-Bench Pro",
"score": 46.1,
"source": "https://labs.scale.com/leaderboard/swe_bench_pro_public",
"metric": "resolve rate",
"dataset": "public"
},
{
"name": "SWE-Atlas Codebase QnA",
"score": 13.5,
"source": "https://labs.scale.com/leaderboard/sweatlas-qna",
"metric": "score",
"harness": "Mini-SWE-Agent"
},
{
"name": "SWE-Atlas Refactoring",
"score": 33.81,
"source": "https://labs.scale.com/leaderboard/sweatlas-refactoring",
"metric": "score",
"harness": "Gemini CLI"
},
{
"name": "SWE-Atlas Test Writing",
"score": 29.84,
"source": "https://labs.scale.com/leaderboard/sweatlas-tw",
"metric": "score",
"harness": "Mini-SWE-Agent"
},
{
"name": "Artificial Analysis Coding Agent Index",
"score": 43,
"source": "https://artificialanalysis.ai/agents/coding-agents",
"metric": "average pass@1",
"harness": "Gemini CLI",
"variant": "high"
},
{
"name": "SWE-Atlas Codebase QnA",
"score": 45.6,
"source": "https://artificialanalysis.ai/agents/coding-agents",
"metric": "pass@1",
"harness": "Gemini CLI",
"variant": "high"
},
{
"name": "SWE-Bench Pro",
"score": 15.1,
"source": "https://artificialanalysis.ai/agents/coding-agents",
"metric": "pass@1",
"harness": "Gemini CLI",
"variant": "high",
"dataset": "hard-aa"
},
{
"name": "Terminal-Bench",
"score": 68.3,
"source": "https://artificialanalysis.ai/agents/coding-agents",
"metric": "pass@1",
"harness": "Gemini CLI",
"variant": "high",
"version": "2.1"
},
{
"name": "GPQA Diamond",
"score": 94.3,
"source": "https://openai.com/index/introducing-gpt-5-5/",
"metric": "accuracy",
"date": "2026-04-23"
},
{
"name": "Humanity's Last Exam",
"score": 44.4,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "accuracy",
"dataset": "full set, text + MM",
"date": "2026-05-19"
},
{
"name": "ARC-AGI-2",
"score": 77.1,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "accuracy",
"date": "2026-05-19"
},
{
"name": "MMMU Pro",
"score": 80.5,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "accuracy",
"variant": "no tools",
"date": "2026-05-19"
},
{
"name": "MCP Atlas",
"score": 78.2,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "success rate",
"date": "2026-05-19"
},
{
"name": "OSWorld-Verified",
"score": 76.2,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "success rate",
"date": "2026-05-19"
},
{
"name": "CharXiv Reasoning",
"score": 83.3,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "accuracy",
"variant": "no tools",
"date": "2026-05-19"
},
{
"name": "GDPval-AA",
"score": 1314,
"source": "https://deepmind.google/models/gemini/flash/",
"metric": "Elo",
"date": "2026-05-19"
}
],
"release_date": "2026-02-19",
"open_weights": false
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| google-vertex/global/flex | 1.0M | $1.00 | $6.00 | $0.10 | $0.19 | 99.47% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global/flexBatch pricing | 1.0M | $1.00 | $6.00 | $0.10 | $0.19 | 99.47% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/flex | 1.0M | $1.00 | $6.00 | $0.10 | $0.19 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/flexBatch pricing | 1.0M | $1.00 | $6.00 | $0.10 | $0.19 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global | 1.0M | $2.00 | $12.00 | $0.20 | $0.38 | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/globalBatch pricing | 1.0M | $2.00 | $12.00 | $0.20 | $0.38 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio | 1.0M | $2.00 | $12.00 | $0.20 | $0.38 | 97.56% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studioBatch pricing | 1.0M | $2.00 | $12.00 | $0.20 | $0.38 | 97.56% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global/priority | 1.0M | $3.60 | $21.60 | $0.36 | $0.68 | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global/priorityBatch pricing | 1.0M | $3.60 | $21.60 | $0.36 | $0.68 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priority | 1.0M | $3.60 | $21.60 | $0.36 | $0.68 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priorityBatch pricing | 1.0M | $3.60 | $21.60 | $0.36 | $0.68 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Text provenance
Gemini app/webGoogle SynthID text watermarking
Google DeepMind says text generated in the Gemini app and web experience is watermarked with SynthID by adjusting token probabilities.
Official explanation