LLM Comparison

Claude Opus 4.8 vs GPT-5.3 Codex: benchmark scores, pricing & comparison.

Side-by-side Claude Opus 4.8 vs GPT-5.3 Codex comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #6 vs #27AskClash overall scores 75.6 vs 43.4.
Pricing $5.00/$25.0 vs $1.75/$14.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs OpenAI.

Claude Opus 4.8 vs GPT-5.3 Codex benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricClaude Opus 4.8GPT-5.3 Codex
Overall Score75.643.4
Leaderboard Rank#6#27
RWT9.08.0
Coding Agent Index72.5
HLE57.9
GPQA93.6
IFEval62.2
SWE-bench88.685.0
SWE-Pro69.256.8
SWE-Atlas82.5
Terminal-Bench74.677.3
DeepSWE59.0
OSWorld83.464.7
MCP Atlas82.2
Finance Agent53.9
CharXiv89.9
ARC-AGI 272.1
Tau294.486.0
Input Price (per 1M tokens)$5.00$1.75
Output Price (per 1M tokens)$25.0$14.0
Context Window1M400K
Benchmarks Published185

Claude Opus 4.8 vs GPT-5.3 Codex head-to-head charts

Claude Opus 4.8 leads 6 and GPT-5.3 Codex leads 1 of 7 shared benchmarks. GPT-5.3 Codex is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 4.8GPT-5.3 Codex
Overall
75.6Claude Opus 4.8
43.4GPT-5.3 Codex
RWT
9.0Claude Opus 4.8
8.0GPT-5.3 Codex
SWE-bench
88.6Claude Opus 4.8
85.0GPT-5.3 Codex
SWE-Pro
69.2Claude Opus 4.8
56.8GPT-5.3 Codex
Terminal-Bench
74.6Claude Opus 4.8
77.3GPT-5.3 Codex
OSWorld
83.4Claude Opus 4.8
64.7GPT-5.3 Codex
Tau2
94.4Claude Opus 4.8
86.0GPT-5.3 Codex
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M
GPT-5.3 Codex
Input$1.75
Output$14.0
Workload$4.55
Context400K

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Claude Opus 4.8 and GPT-5.3 Codex comparisons

Explore how Claude Opus 4.8 and GPT-5.3 Codex stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.