Google DeepMind

Gemini 3.1 Pro Preview

Tool callingStructured outputReasoningImage inputAudio inputVideo inputFile input
Gemini 3.1 Pro Preview launch post cover

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

Official leaderboard
11.7%
pass@1 · highest published configuration
mini-swe-agent · high reasoning
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

EvaluationReported score and source
ARC-AGI-2
77.1%
Third-party evaluator · gemini-3.1-pro-preview
External evaluation via Epoch AI
Original-source terms apply
FrontierMath-2025-02-28-Private
36.9%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
FrontierMath-Tier-4-2025-07-01-Private
16.7%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
FrontierMath-Tier-4-v2-Private
26.8%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
FrontierMath-Tiers-1-3-v2-Private
59.6%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
GPQA diamond
94.1%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
GPQA diamond
94.4%
Epoch AI · gemini-3.1-pro-preview_high
Reasoning effort: high
Epoch AI evaluation
OTIS Mock AIME 2024-2025
95.6%
Epoch AI · gemini-3.1-pro-preview
Epoch AI evaluation
OTIS Mock AIME 2024-2025
95.6%
Epoch AI · gemini-3.1-pro-preview_high
Reasoning effort: high
Epoch AI evaluation
SimpleQA Verified
73.5%
Epoch AI · gemini-3.1-pro-preview_high
Reasoning effort: high
Epoch AI evaluation
Terminal Bench
78.4%
Terminal-Bench v2 Leaderboard · gemini-3.1-pro-preview
Agent: Forge Code
Terminal-Bench v2 Leaderboard
Original-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/2.0
Original-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/2.0
Original-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/2.0
Original-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/2.0
Original-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

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

BenchmarkScoreEvaluation detailsEvidence
SWE-Bench Pro54.2 · resolve rate2026-05-28Source
Terminal-Bench70.3 · success rateTerminus-2 · 2.1 · 2026-05-28Source
SWE-Bench Pro46.1 · resolve ratepublicSource
SWE-Atlas Codebase QnA13.5 · scoreMini-SWE-AgentSource
SWE-Atlas Refactoring33.81 · scoreGemini CLISource
SWE-Atlas Test Writing29.84 · scoreMini-SWE-AgentSource
Artificial Analysis Coding Agent Index43 · average pass@1Gemini CLI · highSource
SWE-Atlas Codebase QnA45.6 · pass@1Gemini CLI · highSource
SWE-Bench Pro15.1 · pass@1Gemini CLI · hard-aa · highSource
Terminal-Bench68.3 · pass@1Gemini CLI · high · 2.1Source
GPQA Diamond94.3 · accuracy2026-04-23Source
Humanity's Last Exam44.4 · accuracyfull set, text + MM · 2026-05-19Source
ARC-AGI-277.1 · accuracy2026-05-19Source
MMMU Pro80.5 · accuracyno tools · 2026-05-19Source
MCP Atlas78.2 · success rate2026-05-19Source
OSWorld-Verified76.2 · success rate2026-05-19Source
CharXiv Reasoning83.3 · accuracyno tools · 2026-05-19Source
GDPval-AA1314 · Elo2026-05-19Source
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

All providers
ProviderEndpointContextInput /M tokensOutput /M tokensCached input /M tokensCache write /M tokensUptime 1dData handling
Googlegoogle-vertex/global/flex1.0M$1.00$6.00$0.10$0.1999.47%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Googlegoogle-vertex/global/flexBatch pricing1.0M$1.00$6.00$0.10$0.1999.47%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studio/flex1.0M$1.00$6.00$0.10$0.19100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studio/flexBatch pricing1.0M$1.00$6.00$0.10$0.19100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Googlegoogle-vertex/global1.0M$2.00$12.00$0.20$0.38100.00%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Googlegoogle-vertex/globalBatch pricing1.0M$2.00$12.00$0.20$0.38100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studio1.0M$2.00$12.00$0.20$0.3897.56%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studioBatch pricing1.0M$2.00$12.00$0.20$0.3897.56%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Googlegoogle-vertex/global/priority1.0M$3.60$21.60$0.36$0.68100.00%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Googlegoogle-vertex/global/priorityBatch pricing1.0M$3.60$21.60$0.36$0.68100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studio/priority1.0M$3.60$21.60$0.36$0.68100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Google AI Studiogoogle-ai-studio/priorityBatch pricing1.0M$3.60$21.60$0.36$0.68100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Provider data:OpenRouter

Text provenance

Gemini app/web

Google 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