LLM Comparison

Claude Fable 5 vs GPT-5.3 Codex: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5 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 #2 vs #27AskClash overall scores 85.5 vs 43.4.
Pricing $10.0/$50.0 vs $1.75/$14.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs OpenAI.

Claude Fable 5 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 Fable 5GPT-5.3 Codex
Overall Score85.543.4
Leaderboard Rank#2#27
RWT9.08.0
Coding Agent Index77.2
HLE64.5
GPQA94.5
IFEval80.3
SWE-bench95.585.0
SWE-Pro80.356.8
SWE-Atlas83.3
Terminal-Bench88.077.3
DeepSWE69.7
OSWorld85.064.7
Finance Agent56.3
CharXiv93.5
MMMU-Pro92.7
Tau289.286.0
Input Price (per 1M tokens)$10.0$1.75
Output Price (per 1M tokens)$50.0$14.0
Context Window1M+400K
Benchmarks Published175

Claude Fable 5 vs GPT-5.3 Codex head-to-head charts

Claude Fable 5 leads 7 and GPT-5.3 Codex leads 0 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 Fable 5GPT-5.3 Codex
Overall
85.5Claude Fable 5
43.4GPT-5.3 Codex
RWT
9.0Claude Fable 5
8.0GPT-5.3 Codex
SWE-bench
95.5Claude Fable 5
85.0GPT-5.3 Codex
SWE-Pro
80.3Claude Fable 5
56.8GPT-5.3 Codex
Terminal-Bench
88.0Claude Fable 5
77.3GPT-5.3 Codex
OSWorld
85.0Claude Fable 5
64.7GPT-5.3 Codex
Tau2
89.2Claude Fable 5
86.0GPT-5.3 Codex
Claude Fable 5
Input$10.0
Output$50.0
Workload$20
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 Fable 5 and GPT-5.3 Codex comparisons

Explore how Claude Fable 5 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.