What are the verified coding and reasoning benchmarks for Gemini 3.1 Pro Preview?

Gemini 3.1 Pro Preview achieves SWE-bench Verified: 71% (Thinking), LiveCodeBench: 62.4%, AIME: 86.5%. Verified sources: Gemini 3.1 Pro Capabilities and Evaluations (Google DeepMind).

How does Gemini 3.1 Pro Preview compare to rival frontier coding models on SWE-bench and pricing?

Gemini 3.1 Pro Preview achieves SWE-bench Verified: 71% at $2.5/$10 per 1M tokens. Direct peer comparison: Claude 3.7 Sonnet (70.3% SWE-bench, $3/$15); OpenAI o3 (71.7% SWE-bench, $5/$20); xAI Grok 4.20 (58.5% SWE-bench, $2/$8); Gemini 3.7 Flash (67.1% SWE-bench, $0.15/$0.6).

Does Swarm isolate Gemini 3.1 Pro Preview code edits from other agents?

Yes. Swarm provisions isolated Git worktrees for every session and subagent, preventing file race conditions and keeping your main working tree clean until verification passes.

Can Gemini 3.1 Pro Preview be assigned to specific subagent roles?

Yes. In ~/.swarm/config.json, you can configure Gemini 3.1 Pro Preview as Primary/Planner (DAG task decomposition), Coder (implementation in isolated worktrees), or Finder (read-only symbol search).

Gemini 3.1 Pro Preview — Specs, Context & Capabilities

Q: What is the recommended Swarm multi-agent topology for Gemini 3.1 Pro Preview?

Swarm recommends Gemini 3.1 Pro Preview as Primary / Planner (Tier 1: Frontier Large-Context Architect). Supreme context window capacity allows analyzing multi-package architecture and drafting complex Task Program DAGs. Best paired with: Gemini 3.8 Flash for subagent implementation.

Q: How do I run Gemini 3.1 Pro Preview with Swarm?

Configure Gemini 3.1 Pro Preview via CLI using: swarm ctl model set --provider google --model google/gemini-3.1-pro-preview, or switch models interactively inside the terminal TUI with /models.

Gemini 3.1 Pro Preview Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified

SWE-bench Verified

71%

ThinkingGoogle DeepMind Technical Card ↗

LiveCodeBench

62.4%

ThinkingLiveCodeBench ↗

LMSYS Coding Elo

1395Elo

Coding ArenaLMSYS Arena ↗

AIME 2024 / 2025

86.5%

ThinkingGoogle DeepMind Technical Card ↗

Pricing ($ / 1M tokens)

$2.5/ $10

$0.35 cached readStandard API Pricing

What This Means in Real Software Development

71.0% on SWE-bench Verified with deep internal chain-of-thought reflection.
Massive 2M token context window ingests entire enterprise monorepos without loss of detail.
86.5% on AIME 2024 demonstrates superior multi-step deductive problem solving.
Priced at $2.50/M input, providing frontier reasoning at 1/6th the cost of older frontier models.

Swarm Multi-Agent Topology

Tier 1: Frontier Large-Context ArchitectRole: Primary / Planner

Best Paired With: Gemini 3.8 Flash for subagent implementation

Supreme context window capacity allows analyzing multi-package architecture and drafting complex Task Program DAGs.

Git Worktree Isolation Advantage:

Supervises worktree integrations and validates commit diffs before merging.

What Developers & Practitioners Are Saying

Real-world field observations, production strengths, and developer consensus

Field Consensus

"Preview build showcasing enhanced agentic planning and tighter tool integration from Google DeepMind."

Verified Real-World Strengths

Improved tool calling stability over 2.5 Pro
Lower first-token latency on large context prompts
Enhanced algorithmic accuracy on LiveCodeBench (42.8%)

Production Caveats & Gaps

Preview status means occasional endpoint rate-limit shifts
Requires rigorous post-processing on git diff syntax

Primary Sources & Methodology Citations

Gemini 3.1 Pro Capabilities and Evaluations — Google DeepMind (February 2026)

Head-to-Head Frontier Comparisons: Gemini 3.1 Pro Preview vs Rivals

Standardized, side-by-side benchmark & economics comparison against peer models

Flagship Comparative Matrix

Model	Role / Tier	SWE-bench	LiveCodeBench	LMSYS Elo	AIME	Input / Output
Gemini 3.1 Pro PreviewGoogle GeminiCurrent	Tier 1: Frontier Large-Context Architect	71%	62.4%	1395	86.5%	$2.5 / $10
Claude 3.7 SonnetAnthropic Compare Gemini 3.1 Pro Preview vs Claude 3.7 Sonnet →	Tier 1: Frontier Architect & Planner	70.3%	59.2%	1390	80%	$3 / $15
OpenAI o3OpenAI Compare Gemini 3.1 Pro Preview vs OpenAI o3 →	Tier 1: Frontier Architect & Deductive Specialist	71.7%	76.2%	1415	92.4%	$5 / $20
xAI Grok 4.20xAI Compare Gemini 3.1 Pro Preview vs xAI Grok 4.20 →	Tier 1: Frontier Systems Specialist	58.5%	54.2%	1375	76%	$2 / $8
Gemini 3.7 FlashGoogle Compare Gemini 3.1 Pro Preview vs Gemini 3.7 Flash →	Tier 3: High-Throughput Subagent Engine	67.1%	51.9%	1370	81.5%	$0.15 / $0.6

Explore All AI Model Comparisons Hub (Gemini 3.1 Pro Preview & Flagship Peers) →

Gemini 3.1 Pro Preview model overview

Gemini 3.1 Pro Preview is listed in the public Swarm catalog through Google Gemini. This page summarizes the verified catalog fields used by Swarm without claiming real-time access for every provider account.

Provider: Google Gemini
Family: Gemini
Context window: 1.05M tokens
Thinking support: low · medium · high
Availability status: Preview
Catalog ID: google/gemini-3.1-pro-preview

Audio input
File input
Image input
Text input
Video input
Text output
Reasoning
Batch
Preview

Run Gemini 3.1 Pro Preview in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →

bash — swarm run

$swarm ctl model set --provider google --model google/gemini-3.1-pro-preview

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign Gemini 3.1 Pro Preview to specialized system roles in ~/.swarm/config.json:

Primary / Planner: Orchestrates full task DAGs and multi-stage pipelines.
Coder Subagent: Generates code and unit tests inside private Git worktrees.
Finder Subagent: Performs read-only code search, symbol discovery, and mapping.

System Agent Roles →Why Swarm Architecture →