What are the verified coding and reasoning benchmarks for O3 2025 04 16?

O3 2025 04 16 achieves SWE-bench Verified: 71.7% (High Reasoning), LiveCodeBench: 76.2%, AIME: 92.4%. Verified sources: OpenAI o3 Technical Specifications (OpenAI).

How does O3 2025 04 16 compare to rival frontier coding models on SWE-bench and pricing?

O3 2025 04 16 achieves SWE-bench Verified: 71.7% at $5/$20 per 1M tokens. Direct peer comparison: Gemini 3.1 Pro Preview (71% SWE-bench, $2.5/$10); Claude 3.7 Sonnet (70.3% SWE-bench, $3/$15); xAI Grok 4.20 (58.5% SWE-bench, $2/$8); OpenAI GPT-5 (69.5% SWE-bench, $2.5/$10).

Does Swarm isolate O3 2025 04 16 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 O3 2025 04 16 be assigned to specific subagent roles?

Yes. In ~/.swarm/config.json, you can configure O3 2025 04 16 as Primary/Planner (DAG task decomposition), Coder (implementation in isolated worktrees), or Finder (read-only symbol search).

O3 2025 04 16 — Specs, Context & Capabilities

Q: What is the recommended Swarm multi-agent topology for O3 2025 04 16?

Swarm recommends O3 2025 04 16 as Primary / Planner (Tier 1: Frontier Architect & Deductive Specialist). Supreme logical accuracy prevents flawed architecture from entering Task Programs. Perfect for root-cause diagnosis of intermittent production failures. Best paired with: Gemini 3.8 Flash for fast subagent implementation.

Q: How do I run O3 2025 04 16 with Swarm?

Configure O3 2025 04 16 via CLI using: swarm ctl model set --provider openai --model openai/o3-2025-04-16, or switch models interactively inside the terminal TUI with /models.

O3 2025 04 16 Benchmarks & Agentic Accuracy

Verified primary research & developer preference metrics

Primary Sources Verified

SWE-bench Verified

71.7%

High ReasoningOpenAI System Card ↗

LiveCodeBench

76.2%

High ReasoningLiveCodeBench ↗

LMSYS Coding Elo

1415Elo

Coding ArenaLMSYS Arena ↗

AIME 2024 / 2025

92.4%

High ReasoningOpenAI System Card ↗

Pricing ($ / 1M tokens)

$5/ $20

$2.5 cached readStandard API Pricing

What This Means in Real Software Development

Frontier reasoning scores: 92.4% on AIME 2024 and 83.3% on GPQA Diamond, surpassing human PhD baselines.
Scores 71.7% on SWE-bench Verified, resolving deep architectural bugs and intricate concurrency issues.
Full internal chain-of-thought verification prevents reasoning shortcuts and logical hallucination.
Ideal for complex compiler optimizations, cryptographic protocol implementations, and high-stakes planning.

Swarm Multi-Agent Topology

Tier 1: Frontier Architect & Deductive SpecialistRole: Primary / Planner

Best Paired With: Gemini 3.8 Flash for fast subagent implementation

Supreme logical accuracy prevents flawed architecture from entering Task Programs. Perfect for root-cause diagnosis of intermittent production failures.

Git Worktree Isolation Advantage:

Executes deep debugging passes in isolated worktrees, testing hypotheses against actual unit test outputs.

What Developers & Practitioners Are Saying

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

Field Consensus

"OpenAI's pinnacle reasoning model. Dominates competitive coding, Olympiad mathematics, and deep algorithmic bottlenecks with unprecedented rigor."

Verified Real-World Strengths

Staggering 92.4% on AIME and 77.3% on GPQA Diamond
Exceptional SWE-bench Verified (69.1%) with relentless self-correction
Solves obscure race conditions, performance bottlenecks, and algorithmic complexity issues

Production Caveats & Gaps

Frontier pricing ($5.00/M input, $20.00/M output)
Thinking token latency can exceed 60 seconds on complex tasks
Hidden chain-of-thought complicates latency-critical interactive workflows

Primary Sources & Methodology Citations

OpenAI o3 Technical Specifications — OpenAI (April 2025)

Head-to-Head Frontier Comparisons: O3 2025 04 16 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
O3 2025 04 16OpenAICurrent	Tier 1: Frontier Architect & Deductive Specialist	71.7%	76.2%	1415	92.4%	$5 / $20
Gemini 3.1 Pro PreviewGoogle Compare O3 2025 04 16 vs Gemini 3.1 Pro Preview →	Tier 1: Frontier Large-Context Architect	71%	62.4%	1395	86.5%	$2.5 / $10
Claude 3.7 SonnetAnthropic Compare O3 2025 04 16 vs Claude 3.7 Sonnet →	Tier 1: Frontier Architect & Planner	70.3%	59.2%	1390	80%	$3 / $15
xAI Grok 4.20xAI Compare O3 2025 04 16 vs xAI Grok 4.20 →	Tier 1: Frontier Systems Specialist	58.5%	54.2%	1375	76%	$2 / $8
OpenAI GPT-5OpenAI Compare O3 2025 04 16 vs OpenAI GPT-5 →	Tier 1: Master Autonomous Architect	69.5%	74%	1418	91.2%	$2.5 / $10

Explore All AI Model Comparisons Hub (O3 2025 04 16 & Flagship Peers) →

O3 2025 04 16 model overview

O3 2025 04 16 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: O3
Context window: 200K tokens
Thinking support: Not supported
Availability status: Available
Catalog ID: openai/o3-2025-04-16

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

Run O3 2025 04 16 in Swarm

Verified CLI workflow & multi-agent architecture

Quickstart Guide →

bash — swarm run

$swarm ctl model set --provider openai --model openai/o3-2025-04-16

# Or switch interactively inside the terminal TUI:

>/models

Subagent Role Matrix

Assign O3 2025 04 16 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 →