Claude Fable 5 vs Claude Opus 4.7:2026年に勝つAIモデルはどっち?

“I do medical imaging research and the bio classifier keeps flagging my MRI segmentation prompts, then it silently falls back to Opus 4.8 mid-session. At $50 per million output tokens I expect to at least know which model actually answered me.”

“Yes it's 2x the price of Opus and yes the turns are slow. But one overnight Fable run replaced what used to be a week of supervising shorter runs. On a per-task basis it's actually the cheapest model we use.”

“The 1M context is real, not marketing. I fed it our entire service mesh config plus six months of incident postmortems and it traced a flaky timeout to a retry policy nobody remembered writing. Opus 4.8 never connected those dots.”

“Gave it a monorepo migration that Opus 4.8 kept stalling on. It ran for about 40 minutes, came back with the whole thing done plus a test harness it wrote for itself. Felt like reviewing a senior engineer's PR, not babysitting a chatbot.”

“Watch your invoices. New tokenizer counts ~30% more tokens for the same text, and it narrates every tiny step. Sticker price unchanged, effective cost definitely not.”

“Came from 4.6 and stopped chunking repos entirely. 1M context, 128K output, flat $5/$25 with no long-context premium. That pricing decision alone won me over.”

“87.6 SWE-bench Verified is not just marketing, it closes tickets GPT-5.4 fumbles. And the hi-res vision with pixel-accurate coords finally makes screenshot debugging useful.”