Quick Take
OpenAI’s GPT-5.6 Luna (low) and Anthropic’s Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) represent two distinct approaches to AI deployment. GPT-5.6 Luna emphasizes speed and affordability, whereas Claude Fable 5 prioritizes raw intelligence and technical depth.
Benchmark Read
Claude Fable 5 consistently outperforms GPT-5.6 Luna across all shared metrics. In the Intelligence index, Claude Fable 5 scores 59.9 compared to Luna’s 33.3. The gap is even more pronounced in coding, where Claude Fable 5 achieves a 76.5 index score against Luna’s 44.2.
Specific benchmark results further illustrate this divide:
- GPQA: Claude Fable 5 (0.926) vs. GPT-5.6 Luna (0.835)
- HLE: Claude Fable 5 (0.533) vs. GPT-5.6 Luna (0.188)
- SciCode: Claude Fable 5 (0.602) vs. GPT-5.6 Luna (0.456)
- LCR: Claude Fable 5 (0.7) vs. GPT-5.6 Luna (0.593)
Claude Fable 5 also demonstrates high proficiency in specialized benchmarks like TAU2 (0.985) and TerminalBench Hard (0.628).
Cost and Speed
There is a significant trade-off between performance and efficiency. GPT-5.6 Luna is highly optimized for speed, boasting an output of 232.911 tokens/s and a time-to-first-token of 1.032s. Its blended pricing is $2.25/1M tokens.
Conversely, Claude Fable 5 is built for depth rather than immediate responsiveness. It operates at 60.571 tokens/s with a substantial 54.299s time-to-first-token. Its cost is significantly higher, with a blended price of $20.00/1M tokens, reflecting its status as a high-effort reasoning model.
Best Fit
GPT-5.6 Luna is best suited for high-volume applications, real-time chat interfaces, and tasks where cost-per-token is a primary constraint. Claude Fable 5 is the ideal candidate for complex software engineering, advanced scientific research, and agentic workflows that require high reasoning accuracy regardless of latency.
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