Compare · ModelsLive · 2 picked · head to head
Claude Opus 4.6 (Fast) vs GPT-5.3-Codex
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.6 (Fast) wins on 3/4 benchmarks
Claude Opus 4.6 (Fast) wins 3 of 4 shared benchmarks. Leads in speed · agentic.
Category leads
speed·Claude Opus 4.6 (Fast)agentic·Claude Opus 4.6 (Fast)
Hype vs Reality
Attention vs performance
Claude Opus 4.6 (Fast)
#150 by perf·no signal
GPT-5.3-Codex
#101 by perf·no signal
Best value
GPT-5.3-Codex
13.8x better value than Claude Opus 4.6 (Fast)
Claude Opus 4.6 (Fast)
0.5 pts/$
$90.00/M
GPT-5.3-Codex
6.7 pts/$
$7.88/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
OpenAI
$840.0B·Tier 1
Head to head
4 benchmarks · 2 models
Claude Opus 4.6 (Fast)GPT-5.3-Codex
Artificial Analysis · Agentic Index
Claude Opus 4.6 (Fast) leads by +5.4
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
Claude Opus 4.6 (Fast)
67.6
GPT-5.3-Codex
62.2
Artificial Analysis · Coding Index
GPT-5.3-Codex leads by +5.0
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
Claude Opus 4.6 (Fast)
48.1
GPT-5.3-Codex
53.1
Artificial Analysis · Quality Index
Claude Opus 4.6 (Fast) leads by +8.7
Claude Opus 4.6 (Fast)
53.0
GPT-5.3-Codex
44.3
SWE Atlas · Codebase QnA
Claude Opus 4.6 (Fast) leads by +0.7
Claude Opus 4.6 (Fast)
33.3
GPT-5.3-Codex
32.6
Full benchmark table
| Benchmark | Claude Opus 4.6 (Fast) | GPT-5.3-Codex |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 67.6 | 62.2 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 48.1 | 53.1 |
Artificial Analysis · Quality Index | 53.0 | 44.3 |
SWE Atlas · Codebase QnA | 33.3 | 32.6 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $30.00 | $150.00 | 1.0M tokens (~500 books) | $600.00 | |
| $1.75 | $14.00 | 400K tokens (~200 books) | $48.13 |