Anthropic Claude Fable 5.1：降价、零数据留存与能力评测

This is the weirdest situation in which to write a capabilities review.

Introducing the world’s most powerful model, by a substantial margin. No wait, this just in, we also have someone else introducing the world’s most powerful model.

Claude Fable 5.1 and GPT-6 Astra are both excellent models. This much, we know.

Fable 5.1 comes with reduced cache prices, the option of zero data retention and substantially more lenient classifiers than Fable 5.

Early signs are, with large error bars, that the jump from Sol to Astra is bigger and more exciting than the jump from Fable 5 to Fable 5.1. This may be similar to how the scaling move from Opus to Fable was a big deal.

With the exception of token use, Fable 5.1 got almost universally positive feedback in absolute terms. Reports are that Fable 5.1 is highly well-rounded. Writing is greatly improved. The Claudisms seem to have improved, although some are very much still there. It admits mistakes. People enjoy their conversations. Several people noted it simplifies code. The safety classifiers are less obnoxious.

Fable 5.1 loves being proactive and doing all the things. If you give it a high effort level, it will find things to do with those tokens. Often they will be useful things.

My own experience has been that Fable 5.1 and Astra are both excellent. In the one case I’ve had the chance to compare responses on a hard question, both answers were different and very good, complementing each other. My plan is to ‘dual wield’ and ask both all non-trivial queries, at least for a while.

Mostly this review of necessity looks at Fable 5.1 in isolation, rather than being able to compare it to Astra, and most of those who react are doing likewise. There will be full coverage of Astra in turn, which will give more opportunity for comparisons.

Concept by Fable 5.1, executed by Gemini

Table of Contents

• The Official Pitch.
• Our Price Cheap.
• Zero Data Retention and Reduced Safeguards.
• Official Benchmarks.
• Other People’s Benchmarks.
• The System Prompt.
• The Blurb Pitches.
• The Every Review Is In and It’s Very Good.
• Positive Reactions.
• Our Price Cheap But Only Per Token.
• Negative Reactions.
• Early Whispers.
• Weapon of Choice.

The Official Pitch

As usual, Anthropic basically said ‘here is the new model with the higher number.’

The coding department thinks it is very good at coding, also Our Price Cheap.

Boris Cherny (Claude Code Creator, Anthropic): Fable 5.1 is our best model yet for coding, data analysis, computer use, design, presentations, Tag, and the hardest long-running agentic work.

This model is a pleasure to work with, and I’ve been using it for everything.

We have also reduced prices for Enterprise, API, and SDK customers. Cache reads on Fable 5.1 are now $0.25 per million tokens (previously: $1). Up to 38% cheaper for a typical Claude Code session.

We have been working on how often safeguards intervene. Our latest biology safeguards intervene on benign requests 85% less often than the ones we shipped with Fable 5, and Claude Code users should see around 60% fewer cyber interventions per session. Expect more improvements soon.

Last but not least, Fable 5.1 writes better and has better tone. We heard your feedback, and are actively working on reducing Claude-speak. Solid progress with 5.1, more to come.

Alex Albert highlights its ability to generate videos through code. His example is he took a picture of a property lot, and told Fable to design a house, render it, and produce a cinematic walkthrough, short video at link.

They spend a section on scientific research. That’s also an OpenAI point of emphasis.

Our Price Cheap

Anthropic is doing a strange thing with Fable 5.1 pricing. The headline price is unchanged from Fable 5, but the effective price is lower because they are reducing the pricing on cache reads from $1 to $0.25 per million tokens.

This will lower typical per-token costs by 25% and highly agentic work costs by ‘up to approximately 45%,’ consistent with Boris’s 38% cheaper for typical Claude Code use:

I presume this aligns incentives, by lining up with actual costs, but I would have been inclined to put some of the discount in headline costs instead. People are simple creatures, you have to talk to them on their level sometimes.

LLM Index: Claude Fable 5.1 is live on OpenRouter.

Anthropic’s new model arrives at $10.00/M input, $50.00/M output.

No predecessor price or history hook attached. The clean read is the listing itself: a premium Claude shelf entry, now priced on OpenRouter.

Zero Data Retention and Reduced Safeguards

Fable 5 never got above about 11% of Anthropic dollar spend on Ramp, despite being the clearly best model out there.

Two of the big objections were the safeguards having a large blast radius that stopped ordinary work, and companies, often due to various regulatory concerns, failing to abide Anthropic’s data retention policy, where they required records be kept for 30 days.

The individual Dude, who could abide, had huge coding edge.

Anthropic has heard you, and had some time to get more comfortable, and for the government to calm down versus when it was so nervous it forced Fable offline over a supposed ‘jailbreak.’ Anthropic is working on a new system that will allow ‘eligible customers’ to use Fable 5.1 with zero outside data retention, via letting the customer store the data. Until then, full zero data retention is available for those customers.

They’ve greatly reduced the false positive rate on the classifiers (at least 60%).

That is too many changes at once, including model improvements and lower prices, but will be a fascinating natural experiment. We should see massive adoption of Fable 5.1 within the Anthropic ecosystem, far more than the 11% for Fable 5. If we do not, then people really are purely balking at the headline price without thinking that through.

Official Benchmarks

Anthropic shares a ton of benchmarks. Mostly we see modest improvement from Fable 5 or Opus 5 to Fable 5.1, with some small regressions. I’m listing them so you can get a quick gestalt. There does not seem to be a clear pattern.

Fable 5.1 came out prior to GPT-6, so here is where things stood at that time.

All ‘slash line’ scores I give, e.g. 50%/70%, refer to scores without and then with tools.

All improvement or regression numbers by default are versus the best score of either Opus 5 or Mythos 5.

All numbers are rounded to the given significant figures, as per my judgment.

Life sciences evals overall show modest improvement and are covered in post one.

Parenthesis on Terminal Bench 4.0 is for Mythos, other scores are for Fable.

I have added Astra to the chart, based on what we could find.

The Anthropic ECI score is 162.0, versus 159.5 for Mythos 5 and 160.7 for Opus 5, exactly on the Mythos-era trend line.

DeepSWE v1.1 score was 67.4% over 5 trials, but with no frame of reference.

FrontierCode 1.1 Extended scores are worse at higher effort levels. Anthropic attributes that to Fable 5.1 being unable to stop itself from making additional helpful edits at higher effort levels, which get it marked as incorrect.

FrontierSWE v2 score was 0.57 versus 0.52 for Opus 5, 0.48 for Fable 5 and 0.32 for Sol.

Terminal-Bench-Science 0.1 was a big jump to 52.6% from 24.7%.

CursorBench 3.2 maxed out at 73.4% versus a max out of 70.5% for Fable 5, at a substantially lower total cost. Sol maxes out at 67.2%.

CritPT-Corrected slightly improved from 85.5% to 88.4%.

ArXivMath slightly improved from 91%/91% to 91%/94%.

ProgramBench improved slightly from 86.3% to 87.6%.

As per the chart, Humanity’s Last Exam improved from 57.8%/63.8% to 60.9%/65%.

They run various multi-agent tests, but don’t provide good points of comparison, so I can’t tell how good the results are.

Chartography improved from 37%/84% to 43%/86%.

BenchCAD Vision2Code improved from 38%/67% to 44%/84%.