Claude Fable 5.1 and Claude Mythos 5.1
TL;DR Highlight
Fable 5.1 cuts typical cost about 25% via cheaper cache reads and improves coding benchmarks.
Who Should Read
A backend developer running coding agents on the Claude API who is weighing a model switch and cost optimization.
Core Mechanics
- Fable 5.1 and Mythos 5.1 are the same model
- Only the safeguard level differs.
- Fable 5.1 is generally available while Mythos 5.1 is limited to trusted access programs.
- Cheaper cache reads cut the bill
- Token-billed typical workloads cost an estimated 25% less than Fable 5.
- Highly agentic work often saves more, up to about 45%.
- Low or Medium effort matches Fable 5
- At Low or Medium effort it reaches results similar to or better than Fable 5 at much lower cost.
- Claude Code defaults to High, while Claude Cowork and Claude.ai default to Medium.
- Benchmarks rose over Fable 5
- Terminal-Bench 4.0 is 55.8% versus 42.0% for Fable 5.
- CursorBench 3.2.0 is 73.4% versus 70.5% for Fable 5.
- Terminal-Bench-Science 0.1 is 52.6% versus 24.7% for Fable 5.
Community Reactions
- Whole-file rewrites flagged
- A commenter noted the changelog says the model is more likely to rewrite whole files for small edits, costing more output tokens and time.
- The suggested fix is adding the official docs' "edit surgically" instruction to the system prompt.
- Usage limits burned fast
- Commenters reported hitting the 5-hour limit before finishing a first task on both Team Premium and Max 20x accounts.
- One said a multi-hour run felt plodding and took another 1h15m just to wrap up.
- Pushback on the size of the gain
- One commenter argued that without Terminal-Bench-Science the gain over Opus 5 is only 1.5 to 3.5 points.
- Another said Artificial Analysis shows Fable 5.1 costing more than 5.0.
- Token budgets matter more than models
- One commenter said predictable spend within monthly quotas matters more than a better model.
- Another said cheap models like DeepSeek V4 Flash or GLM 5.3 Flash are good enough.
How to Apply
- Add a surgical-edit instruction
- Append the instruction in the prompt below to your coding agent's system prompt today.
- Run the same edit task before and after and compare output tokens.
- Compare cost at Low and Medium effort
- Run a few existing Fable 5 or Opus 5 tasks on Fable 5.1 at Low and Medium.
- Log cost per task and quality in a table to choose your default effort.
- Migrate cache-heavy agents first
- Move workloads that reread the same context, such as code review or long-running agents.
- Check the change in cache read cost on your bill before and after.
- Re-measure false positives on security tooling
- Rerun vulnerability analysis prompts that safeguards blocked before.
- Record the block rate.
Try It
# Paste at the end of your Claude Code or API system prompt (instruction quoted from the official docs via a comment)
The number of tokens used to edit files is best minimized, all else being equal. Therefore, when it will not affect the end result, try to surgically edit a file rather than rewrite the entire thing.
# Before and after adding this, give {{file}} the same small edit {{request}} and compare output token counts.Terminology
Related Papers
Mercury 3: Diffusion at scale
Scaling diffusion LLM 40x gives Mercury 3: 4–8x faster than speed-tier models, similar quality
Timestral: Mistral's time-series foundation models
A 209M time-series model ranks first on three benchmarks and runs on CPU.
DeepSeek V4.1 Flash 1017 (Max)
DeepSeek V4.1 Flash 1017 Max scores 45 on the Intelligence Index at 211 tok/s and $0.30 input.
If you don't run your own LLM proxy, how do you know whats going on?
Running your own LLM proxy shows which keys, models, and cache misses drive your usage.
DeepSeek: DeepSeek v4.1 Flash 1017
DeepSeek V4.1 Flash 1017: $0.05/M input, 1M context, built for agents
DeepSeek-v4.1-Flash-1017
DeepSeek V4.1 Flash minor update lifts coding and agent benchmarks while cutting run time and output length
Show HN: Llmspeed – feel how fast a local LLM runs before you buy the hardware