What are the verified coding and reasoning benchmarks for OpenAI: o1?

OpenAI: o1 achieves SWE-bench Verified: 48.9% (Standard Reasoning), LiveCodeBench: 61.7%, AIME: 83.3%. Verified sources: OpenAI o1 System Card (OpenAI).

Does Swarm isolate OpenAI: o1 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 OpenAI: o1 be assigned to specific subagent roles?

Yes. In ~/.swarm/config.json, you can configure OpenAI: o1 as Primary/Planner (DAG task decomposition), Coder (implementation in isolated worktrees), or Finder (read-only symbol search).

OpenAI: o1 — Specs, Context & Capabilities

Q: What is the recommended Swarm multi-agent topology for OpenAI: o1?

Swarm recommends OpenAI: o1 as Primary / Planner (Tier 1: Architectural Deductive Planner). High-accuracy reasoning prevents early architectural missteps in large software design tasks. Best paired with: Gemini 3.8 Flash for subagent execution.

Q: How do I run OpenAI: o1 with Swarm?

Configure OpenAI: o1 via CLI using: swarm ctl model set --provider openrouter --model openrouter/openai/o1, or switch models interactively inside the terminal TUI with /models.

OpenAI: o1 Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified

SWE-bench Verified

48.9%

Standard ReasoningOpenAI System Card ↗

LiveCodeBench

61.7%

Standard ReasoningLiveCodeBench ↗

LMSYS Coding Elo

1355Elo

Coding ArenaLMSYS Arena ↗

AIME 2024 / 2025

83.3%

Pass@1OpenAI System Card ↗

Pricing ($ / 1M tokens)

$15/ $60

$3.75 cached readStandard API Pricing

What This Means in Real Software Development

Pioneered large-scale reinforcement learning for step-by-step reasoning and mathematical deduction.
Achieves 75.6% on GPQA Diamond, demonstrating PhD-level scientific reasoning.
Deep chain-of-thought reasoning handles complex edge-case analysis before generating output.
Priced at $15.00/M input and $60.00/M output, optimal for high-stakes problem deconstruction.

Swarm Multi-Agent Topology

Tier 1: Architectural Deductive PlannerRole: Primary / Planner

Best Paired With: Gemini 3.8 Flash for subagent execution

High-accuracy reasoning prevents early architectural missteps in large software design tasks.

Git Worktree Isolation Advantage:

Analyzes complex codebase dependencies inside read-only worktree sessions.

What Developers & Practitioners Are Saying

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

Field Consensus

"The pioneering chain-of-thought reasoning model from OpenAI. Still revered for deep mathematical proofs, though largely superseded by o3 and o3-mini in speed."

Verified Real-World Strengths

Deep multi-step deduction on complex physics and math problems
Strong resilience against adversarial prompting and trick questions
Solid 48.9% on SWE-bench Verified

Production Caveats & Gaps

High latency (no streaming for internal thoughts)
Expensive ($15/M input, $60/M output)
Slower throughput than modern alternatives

Primary Sources & Methodology Citations

OpenAI o1 System Card — OpenAI (December 2024)

OpenAI: o1 model overview

OpenAI: o1 is listed in the public Swarm catalog through OpenRouter. This page summarizes the verified catalog fields used by Swarm without claiming real-time access for every provider account.

Provider: OpenRouter
Family: OpenRouter
Context window: 200K tokens
Thinking support: off
Availability status: Available
Catalog ID: openrouter/openai/o1

File input
Image input
Text input
Text output
Reasoning
Tools
Structured output
JSON

Run OpenAI: o1 in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →

bash — swarm run

$swarm ctl model set --provider openrouter --model openrouter/openai/o1

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign OpenAI: o1 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 →