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Google Gemini model

Gemini 2.5 Pro

Stable release (June 17th, 2025) of Gemini 2.5 Pro

Provider
Google Gemini
Availability
Available
Model ID
gemini-2.5-pro
Snapshot
2026-10-07
Evaluation Verdict

Gemini 2.5 Pro offers an enormous 2M token context window paired with strong multi-turn coding logic (63.8% SWE-bench Verified, 1365 Coding Elo), excelling at whole-repo refactors.

Gemini 2.5 Pro Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified
SWE-bench Verified
63.8%
Standard (2M Context)Google DeepMind Report ↗
LiveCodeBench
50.2%
StandardLiveCodeBench ↗
LMSYS Coding Elo
1365Elo
Coding ArenaLMSYS Arena ↗
AIME 2024 / 2025
76.5%
StandardGoogle DeepMind Report ↗
Pricing ($ / 1M tokens)
$1.25/ $5
$0.31 cached readStandard API Pricing

What This Means in Real Software Development

  • Industry-leading 2M token context window ingests entire repositories and full runtime traces.
  • Scores 63.8% on SWE-bench Verified with native tool use and multi-step deduction.
  • 76.5% on AIME 2024 and 68.2% on GPQA Diamond prove strong analytical and STEM capabilities.
  • Very competitive $1.25/M input pricing for a massive-context frontier model.

Swarm Multi-Agent Topology

Tier 1: Monorepo Architect & PlannerRole: Primary / Planner

Best Paired With: Gemini 3.8 Flash for subagent execution

The best model when planning tasks across massive repositories where the entire dependency graph must fit in context.

Git Worktree Isolation Advantage:

Plans task program barrier stages that subagents implement inside separate worktrees.

What Developers & Practitioners Are Saying

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

Field Consensus

"Google's reliable workhorse for massive context and multimodal reasoning. Unmatched 1M+ token window allows feeding entire codebases without chunking."

Verified Real-World Strengths

  • Industry-leading 1M token context window with high recall
  • Low pricing ($1.25/M input) with 75% prompt caching discount
  • Strong multi-language comprehension and documentation synthesis

Production Caveats & Gaps

  • Can be overly chatty and apologetic on errors
  • SWE-bench score (44.0%) trails Claude 3.7 Sonnet and o3
  • Diffs can occasionally include markdown fences inside code blocks
Benchmark Reality Check

What the benchmark tests: Measures needle-in-a-haystack retrieval and cross-document reasoning across massive contexts.

Production caveat: Avoid feeding raw minified files; structured file trees yield far superior code generation.

Primary Sources & Methodology Citations

Gemini 2.5 Pro model overview

Gemini 2.5 Pro 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
Not supported
Availability status
Available
Catalog ID
google/gemini-2.5-pro
  • Audio input
  • File input
  • Image input
  • Text input
  • Video input
  • Text output
  • Reasoning
  • Batch

Run Gemini 2.5 Pro in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →
bash — swarm run
$swarm ctl model set --provider google --model google/gemini-2.5-pro

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign Gemini 2.5 Pro 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 →
← All Google Gemini models

Public catalog snapshot. Catalog availability is not a real-time provider status or an access guarantee.