LLM Comparison

Claude Fable 5 vs GPT-6 Luna: benchmark scores, pricing & comparison.

Side-by-side Claude Fable 5 vs GPT-6 Luna 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 #43AskClash overall scores 76.5 vs 51.0.
Pricing $10.0/$50.0 vs $0.10/$0.50Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs OpenAI.

Claude Fable 5 vs GPT-6 Luna benchmark comparison

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

MetricClaude Fable 5GPT-6 Luna
Overall Score76.551.0
Leaderboard Rank#2#43
ACB64.650.2
RWT9.0
Coding Agent Index77.2
HLE64.538.5
GPQA94.5
IFEval80.3
SWE-bench95.5
SWE-Pro80.3
SWE-Atlas83.3
Terminal-Bench88.0
DeepSWE69.766.6
GDPval-AA1932.51367.1
OSWorld85.0
Finance Agent56.3
CharXiv93.5
MMMU-Pro89.375.5
Tau289.2
Input Price (per 1M tokens)$10.0$0.10
Output Price (per 1M tokens)$50.0$0.50
Context Window1M+1.05M
Benchmarks Published176

Claude Fable 5 vs GPT-6 Luna head-to-head charts

Claude Fable 5 leads 6 and GPT-6 Luna leads 0 of 6 shared benchmarks. GPT-6 Luna is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Fable 5GPT-6 Luna
Overall
76.5Claude Fable 5
51.0GPT-6 Luna
ACB
64.6Claude Fable 5
50.2GPT-6 Luna
HLE
64.5Claude Fable 5
38.5GPT-6 Luna
DeepSWE
69.7Claude Fable 5
66.6GPT-6 Luna
GDPval-AA
1932.5Claude Fable 5
1367.1GPT-6 Luna
MMMU-Pro
89.3Claude Fable 5
75.5GPT-6 Luna
Claude Fable 5
Input$10.0
Output$50.0
Workload$20
Context1M+
GPT-6 Luna
Input$0.10
Output$0.50
Workload$0.20
Context1.05M

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

More Claude Fable 5 and GPT-6 Luna comparisons

Explore how Claude Fable 5 and GPT-6 Luna 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.