LLM Reference

Claude Opus 4.8 vs GPT-5.3-Codex

Claude Opus 4.8 and GPT-5.3-Codex are the direct 2026 API-model choice for agentic software engineering. Opus is the stronger high-autonomy pick: it leads on SWE-bench Pro, SWE-bench Verified, OSWorld computer use, provider breadth, and 1M-token context. GPT-5.3-Codex is the lower-cost OpenAI-native option, with a narrow Terminal-Bench 2.0 edge and first-class fit for teams already standardized on Codex CLI and OpenAI API workflows.

Pick Claude Opus 4.8 for autonomous repo work, complex multi-file engineering, computer-use agents, and long-context sessions: it leads GPT-5.3-Codex by 12.4 points on SWE-bench Pro and 18.7 points on OSWorld, with 1M context versus 400K. Pick GPT-5.3-Codex for cost-sensitive coding pipelines, OpenAI-native Codex workflows, and terminal automation where its $1.75/M input price and 77.3% Terminal-Bench 2.0 score matter more than the harder agent benchmarks.

Decision scorecard

Local evidence first
SignalClaude Opus 4.8GPT-5.3-Codex
Product typeStandalone API modelCoding-specialized model
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentscustom coding agents, code generation, and tool loops
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1m400k
Cheapest output$25/1M tokens$14/1M tokens
Provider routes6 tracked3 tracked
Shared benchmarksSWE-bench Verified leader2 shared

Decision tradeoffs

Choose Claude Opus 4.8 when...
  • Claude Opus 4.8 holds a shared-benchmark lead on SWE-bench Verified, ahead by 3.6 points.
  • Claude Opus 4.8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Claude Opus 4.8 has broader tracked provider coverage for fallback and route flexibility.
  • Claude Opus 4.8 uniquely exposes Multimodal and Parallel agents in local model data.
  • Local decision data tags Claude Opus 4.8 for Coding, RAG, and Agents.
Choose GPT-5.3-Codex when...
  • GPT-5.3-Codex has the lower cheapest tracked output price at $14/1M tokens.
  • Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate GPT-5.3-Codex

Claude Opus 4.8

$10,250

Cheapest tracked route/tier: Anthropic

GPT-5.3-Codex

$4,900

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $5,350. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Claude Opus 4.8 -> GPT-5.3-Codex
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • GPT-5.3-Codex is $11/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Multimodal and Parallel agents before moving production traffic.
GPT-5.3-Codex -> Claude Opus 4.8
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • Claude Opus 4.8 is $11/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Claude Opus 4.8 adds Multimodal and Parallel agents in local capability data.

Specs

Specification
Released2026-05-282026-02-05
Context window1m400k
Parameters
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
WeightsNot releasedNot released
CodeNot releasedUnknown
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2026-012025-08

Pricing and availability

Pricing attributeClaude Opus 4.8GPT-5.3-Codex
Input price$5/1M tokens$1.75/1M tokens
Output price$25/1M tokens$14/1M tokens
Providers

Capabilities

CapabilityClaude Opus 4.8GPT-5.3-Codex
VisionYesYes
MultimodalYesNo
ReasoningYesYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionYesYes
IDE integrationNoNo
Computer useYesYes
Parallel agentsYesNo

Benchmarks

BenchmarkClaude Opus 4.8GPT-5.3-Codex
SWE-bench Verified88.685.0
SWE-bench Pro69.256.8

Continue comparing

Last reviewed: 2026-07-26. Data sourced from public model cards and provider documentation.