Fable 5.1 (Fully Tested & Real cost comparisons): It's A GREAT Model but there's still ONE ISSUE!
Visit Verdent: https://www.verdent.ai/?id=700712 Visit AISeeKing (my second channel with more cool ai stuff): https://www.youtube.com/@aiseeking In this video, I’ll be reviewing the new Claude Fable 5.1 model, covering its benchmarks, API pricing, cache savings, coding performance, safety changes, and real-world limitations. I’ll also test it across eight KingBench tasks to see how it compares with Fable 5, Opus 5, GPT-5.6 Sol, GLM 5.3, and other leading AI models. -- Key Takeaways: 🚀 Claude Fable 5.1 delivers major improvements in coding, frontend development, 3D generation, and long-horizon agentic tasks. 🏆 It scored 74 out of 80, or 92.5 percent, on KingBench—the highest score achieved by any model tested so far. ⌚ Fable 5.1 set a new record on the difficult 3D wristwatch task, improving from Fable 5’s score of 4 to an impressive 9 out of 10. 💸 API pricing remains at $10 per million input tokens and $50 per million output tokens, while cache-read pricing has been reduced by 75 percent. 📉 Long agentic workloads can be 20 to 45 percent cheaper, but expensive cache writes can still dominate the final bill. 🧠 Always-on adaptive thinking and a 1-million-token context window make the model especially suitable for complex, multi-step projects. 🛡️ Refusals have reportedly been reduced, although security-related requests may still trigger inconsistent behavior or silent Opus fallback. 🔒 New append-only conversation rules, restricted thinking blocks, and other API changes appear designed to prevent model distillation. ✍️ The model’s writing is denser and less polished in some cases, while whole-file rewrites and unbatched tool calls may increase cost and latency. 👍 Overall, Fable 5.1 is an outstanding choice for demanding coding, frontend, 3D, and long-running agentic workloads.
