What are the verified coding and reasoning benchmarks for O4 Mini?

O4 Mini achieves SWE-bench Verified: 56.8% (High Reasoning), LiveCodeBench: 73.4%, AIME: 90.1%. Verified sources: OpenAI o4-mini Technical Preview (OpenAI).

How does O4 Mini compare to rival frontier coding models on SWE-bench and pricing?

O4 Mini achieves SWE-bench Verified: 56.8% at $1.2/$4.8 per 1M tokens. Direct peer comparison: Mistral Devstral 2512 (59.2% SWE-bench, $0.5/$1.5); Llama 4 Maverick (61.2% SWE-bench, $0.8/$2.4); DeepSeek R1 (49.2% SWE-bench, $0.55/$2.19); OpenAI GPT-6 Luna (64.5% SWE-bench, $0.12/$0.48).

How do I run O4 Mini with Swarm?

Configure O4 Mini via CLI using: swarm ctl model set --provider openai --model openai/o4-mini, or switch models interactively inside the terminal TUI with /models.

Does Swarm isolate O4 Mini 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 O4 Mini be assigned to specific subagent roles?

Yes. In ~/.swarm/config.json, you can configure O4 Mini as Primary/Planner (DAG task decomposition), Coder (implementation in isolated worktrees), or Finder (read-only symbol search).

O4 Mini — Specs, Context & Capabilities

Q: What is the recommended Swarm multi-agent topology for O4 Mini?

Swarm recommends O4 Mini as Coder Subagent (Tier 2: High-Speed Deductive Engine). Combines reasoning depth with rapid execution, making it the premier subagent for complex algorithmic implementation jobs in Task Programs. Best paired with: Claude 3.7 Sonnet as Lead Planner.

O4 Mini Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified

SWE-bench Verified

56.8%

High ReasoningOpenAI Technical Preview ↗

LiveCodeBench

73.4%

High ReasoningLiveCodeBench ↗

LMSYS Coding Elo

1385Elo

Coding ArenaLMSYS Arena ↗

AIME 2024 / 2025

90.1%

High ReasoningOpenAI Technical Preview ↗

Pricing ($ / 1M tokens)

$1.2/ $4.8

$0.4 cached readStandard API Pricing

What This Means in Real Software Development

90.1% on AIME and 73.4% on LiveCodeBench with low latency, delivering near-instant deductive code solutions.
56.8% on SWE-bench Verified, outpacing older frontier models like o1 at 1/10th the token cost.
Refined tool-use mechanics enable zero-latency multi-turn agent conversations and automated test suites.
Highly cost-effective ($1.20/M input, $4.80/M output) for parallel subagent swarms.

Swarm Multi-Agent Topology

Tier 2: High-Speed Deductive EngineRole: Coder Subagent

Best Paired With: Claude 3.7 Sonnet as Lead Planner

Combines reasoning depth with rapid execution, making it the premier subagent for complex algorithmic implementation jobs in Task Programs.

Git Worktree Isolation Advantage:

Executes parallel unit test generation and validation across multiple sibling worktrees.

What Developers & Practitioners Are Saying

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

Field Consensus

"Next-generation compact reasoning powerhouse, further compressing the cost and latency of o3-tier deduction for high-concurrency subagents."

Verified Real-World Strengths

56.8% on SWE-bench Verified at lightweight cost ($1.20/M input)
Ultra-fast reasoning output
Refined JSON schema adherence and structured tool calling

Production Caveats & Gaps

Less broad domain breadth than full o3 on obscure academic papers
Requires explicit prompts to balance concise vs detailed responses

Primary Sources & Methodology Citations

OpenAI o4-mini Technical Preview — OpenAI (April 2025)

Head-to-Head Frontier Comparisons: O4 Mini 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
O4 MiniOpenAICurrent	Tier 2: High-Speed Deductive Engine	56.8%	73.4%	1385	90.1%	$1.2 / $4.8
Mistral Devstral 2512Mistral Compare O4 Mini vs Mistral Devstral 2512 →	Tier 2: Dedicated Autonomous Coder	59.2%	54%	1360	71.5%	$0.5 / $1.5
Llama 4 MaverickMeta Compare O4 Mini vs Llama 4 Maverick →	Tier 2: Next-Gen Open Frontier Engine	61.2%	55.4%	1370	78.5%	$0.8 / $2.4
DeepSeek R1DeepSeek Compare O4 Mini vs DeepSeek R1 →	Tier 2: Deep Algorithmic Specialist	49.2%	49.8%	1360	79.8%	$0.55 / $2.19
OpenAI GPT-6 LunaOpenAI Compare O4 Mini vs OpenAI GPT-6 Luna →	Tier 2: Extreme Efficiency Subagent	64.5%	56.8%	1358	—	$0.12 / $0.48

Explore All AI Model Comparisons Hub (O4 Mini & Flagship Peers) →

O4 Mini model overview

O4 Mini is listed in the public Swarm catalog through OpenAI. This page summarizes the verified catalog fields used by Swarm without claiming real-time access for every provider account.

Provider: OpenAI
Family: O4
Context window: 200K tokens
Thinking support: Not supported
Availability status: Available
Catalog ID: openai/o4-mini

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

Run O4 Mini in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →

bash — swarm run

$swarm ctl model set --provider openai --model openai/o4-mini

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign O4 Mini 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 →