Claim◆Article
To avoid burning through valuable Fable tokens before the price increase, tell Fable to hand off smaller tasks to other models, letting it use its own judgement about which model to use.
Jesse Vincent · Simon Willison's Weblog
MechanismArticle
Claude Code's much higher token usage compared to Codex comes from its harness re-feeding a large accumulated context history into the model at each turn, not from generating longer outputs.
Investigating why Claude Code burns far more tokens than Codex or Qwen-Code, Raschka found the difference is almost entirely on the input side—one run used 578k input tokens versus just 4.5k output tokens—suggesting Claude's harness re-accumulates prior context every turn. ✦ AI generated
Sebastian Raschka · Ahead of AI · 2026-06-27 · original ↗
The logs suggest that Claude is repeatedly feeding more context back into the model across turns, including previous messages, tool calls, command outputs, and file contents. For example, one Claude run used about 578k input tokens but only about 4.5k output tokens across 25 turns.
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Claim◆Article
Fable, and to a certain extent Opus, work best when allowed to use their own judgement about how to do a task rather than being given dictated, rigid instructions.
Cat Wu and Thariq Shihipar · Simon Willison's Weblog
Mechanism◆Article
Newer Anthropic models have been specifically trained, presumably via reinforcement learning, to better use the edit tools baked into Claude Code, and this makes them more likely to misuse the differently-shaped custom edit tools of other coding harnesses like Pi.
Armin Ronacher · Simon Willison's Weblog