Claude Fable 5.1 Is Live: Same Price, Cache Reads Cut to a Quarter

Key Takeaways

An upgrade at the same price: $10 input / $50 output per 1M tokens, identical to Fable 5, with capabilities a clear step up
Cache reads cost a quarter: cache reads drop from $1.00 to $0.25 / 1M tokens (0.025x base input, versus 0.1x on other Claude models), which lands directly on long-running agent sessions. APIYI has already matched the cut
Benchmark jumps, not nudges: Terminal-Bench-Science goes from 24.7% to 52.6%, AutomationBench from 17.1% to 31.4% — both more than doubling
⚠️ Three breaking changes: forced tool use (tool_choice of any / tool) now returns 400, thinking blocks are bound to the model that produced them, and editing earlier turns invalidates thinking blocks — read before migrating from Fable 5
Live on APIYI: both claude-fable-5-1 and claude-fable-5-1-thinking, on the OpenAI-compatible and native Anthropic endpoints, in the default / svip / ClaudeCode groups

Background

On September 1, 2026, Anthropic released Claude Fable 5.1 and Claude Mythos 5.1 — the first iteration of the Mythos-class line since Fable 5 launched on June 9. Anthropic positions both as the most advanced models for coding and knowledge work. Unlike the usual generational price bump, Fable 5.1 holds input and output pricing exactly level with Fable 5. The only price change is a 75% cut to cache reads. Anthropic’s own framing: at low and medium effort, Fable 5.1 reaches similar or better results than Fable 5 at a much lower cost — roughly 25% lower overall for typical workloads, and up to 45% lower on agentic tasks. Fable 5.1 and Mythos 5.1 are the same model with different levels of safeguards. Mythos 5.1 is offered only to approved Project Glasswing customers; Fable 5.1 is the publicly available one. APIYI has claude-fable-5-1 and claude-fable-5-1-thinking live, with all four line items — input, output, cache reads, and cache writes — priced exactly in line with the provider, cache reads included at $0.25.

What’s New

Capability gains

Long-horizon agentic coding

Multi-file features, large refactors and migrations, debugging and code review across sessions that run for hours

Documents, spreadsheets, slides

From a first question to a finished document, a live-formula spreadsheet, or a deck built from a blank page

Research and search

Higher accuracy on multistep web research and deep-research tasks that follow up on what they find

Vision

Reads dense charts, filings and tables nested in PDFs, including crop-and-zoom on charts

Long context

Reasons over and connects details across the full 1M token context window

Computer use

Operates browsers and desktop apps more reliably and recovers from failed steps

Benchmark highlights

Official figures (Fable 5.1 vs Fable 5 vs Opus 5):

Benchmark	Fable 5.1	Fable 5	Opus 5	What it measures
Terminal-Bench-Science 0.1	52.6%	24.7%	29.0%	Agentic scientific research
Terminal-Bench 4.0	55.8%	42.0%	52.3%	Agentic coding
AutomationBench	31.4%	17.1%	26.9%	Business workflows
GDPval-AA v2	1853	1723	1824	Knowledge work (score)
OSWorld 2.0 (partial)	77.9%	72.9%	75.4%	Computer use
OSWorld 2.0 (strict)	41.7%	36.1%	39.6%	Computer use
Humanity’s Last Exam (no tools)	60.9%	57.8%	56.6%	Multidisciplinary reasoning
Humanity’s Last Exam (with tools)	65.0%	63.8%	63.6%	Multidisciplinary reasoning
CursorBench 3.2.0	73.4%	70.5%	70.0%	Agentic coding

Terminal-Bench-Science and AutomationBench are the two that more than double — and they map onto exactly the workloads people run in production: long-horizon research agents and business process automation. Multilingual performance is on par with Fable 5.

Specifications

Parameter	Spec
Model ID	`claude-fable-5-1` / `claude-fable-5-1-thinking`
Context window	1,000,000 tokens (default and maximum, standard per-token pricing across the whole window)
Max output	128,000 tokens
Thinking	Adaptive thinking always on, depth steered by the `effort` parameter
Effort levels	`low` / `medium` / `high` / `x-high` / `max`, defaulting to `high`
Tokenizer	Same as Fable 5 (introduced with Opus 4.7); the same text produces roughly 30% more tokens than on older models
Data retention	Inputs and outputs retained for 30 days (abuse detection)
API formats	OpenAI-compatible / native Anthropic

⚠️ Three Breaking Changes (read before migrating)

If you already call claude-fable-5, these three will either error out or change behavior. Check them before you swap the model name.

1. Forced tool use is not supported

tool_choice set to {"type": "any"} or {"type": "tool", "name": "..."} returns a 400 invalid_request_error:

tool_choice: type "tool" and "any" are not supported for this model.

{"type": "auto"} (the default) and {"type": "none"} are unchanged. The same validation applies to the token counting endpoint. Thinking is always on for this model, and a forced tool call would skip it — the model would write its working-out into the tool arguments instead, which lowers argument quality. What to do instead: keep tool_choice: {"type": "auto"} and use strict tool use (strict: true) or structured outputs for schema-valid JSON. To make the model call a tool rather than reply in text, state in the prompt when the tool applies (for example, “Use the get_weather tool to answer”) — Fable 5.1 follows explicit tool instructions reliably.

2. Thinking blocks are tied to the model that produced them

Every thinking block records which model produced it, and it is preserved in one direction only: Fable 5.1 reads earlier models’ thinking blocks, and no earlier model reads Fable 5.1’s. So a conversation that moves onto Fable 5.1 from Opus 5, Fable 5, or any earlier Claude model keeps its reasoning; a conversation that moves from Fable 5.1 back to those models loses it for the turns that run there. When a request carries a block the target model can’t read, the API drops it before the model sees it — dropped blocks don’t count toward input_tokens and aren’t billed.

Worth a close look if your gateway or client does model routing or failure fallback that switches models mid-conversation. The thinking-binding-controls-2026-08-01 beta header surfaces dropped blocks in a top-level input_transformations array; without it, the drop is silent.

3. Editing earlier turns invalidates thinking blocks

Modifying anything before a Fable 5.1 thinking block — the system prompt, the tools array, or an earlier message — errors on the next request with The block is bound to a different conversation. Patterns that invalidate every later thinking block:

Editing, reordering, or removing an earlier turn while keeping later ones
Injecting per-request text into an earlier turn (a reminder or status line) that you remove on the next request
Rebuilding the top-level system prompt or tools array between requests in the same conversation
An image or document URL that serves different bytes on a later request (the check covers the bytes, not the URL, so a rotating signed URL for the same file is fine)

Patterns that keep later blocks valid: removing a leading run of thinking blocks oldest first, letting server-side compaction or context editing trim the history, moving cache_control markers, and changing effort between requests.

The check is enforced for accounts created on or after August 31, 2026. Earlier accounts have the mismatch recorded but not acted on, unless the request sets thinking.block_binding.prefix_mismatch_behavior.Practical rule: treat the conversation as append-only. Add instructions with a turn-scoped system message (clear_at: "next_user_message", beta) and change tools with mid-conversation tool changes rather than editing system or tools. These patterns also keep the prompt cache warm.

New Features (all beta)

Change effort mid-conversation

Raise it for a hard step, lower it for routine ones, without invalidating the prompt cache. Beta header: mid-conversation-output-config-2026-07-01

Turn-scoped system messages

clear_at: "next_user_message" applies for the current turn only; the message stays in messages and is sent back verbatim, so nothing earlier changes. Beta header: mid-conversation-system-clear-at-2026-08-21

Progress updates between tool calls

Set thinking.display to "updates" to receive progress updates as text while reasoning stays hidden. Beta header: thinking-display-updates-2026-08-18

Text generated by Fable 5.1 and Mythos 5.1 also carries Anthropic’s statistical text watermark on every platform, and images and videos retrieved through the Files API carry signed C2PA Content Credentials. Anthropic states the watermark does not change the meaning, quality, or readability of the output, adds no tokens or hidden characters, carries no information about you or your organization, and needs no changes to your requests or responses.

Behavior Differences from Fable 5 (no code change required to notice)

None of these error out, but they change how the model feels. Each has a prompting fix:

Difference	What you see	What to do
Parallel tool calling is more variable	One tool call per turn where Fable 5 batched several. Extra tokens, round trips and wall-clock time, but no loss of answer quality	Add a line asking it to batch independent tool calls in the same turn
Fewer progress updates	Less user-facing text between tool calls, especially at higher effort	Set `thinking.display` to `"updates"`; remove any prompt line telling it to hold findings for the final response
Answers from memory more at low effort	Calls search or retrieval tools less often at the lowest effort	Raise effort for turns that need fresh information, or add a verification nudge
Denser prose	Longer sentences, fewer paragraph breaks	Ask explicitly for paragraphing and pacing
Less formatting in chat	Bold, headers and lists used less than on earlier Claude models	Re-check anti-formatting rules written for older models — they may suppress structure the content needs
Unmarked quotations	When summarizing documents, more likely to reproduce source passages without marking them as quotations	Ask explicitly for quotation marks and source attribution
Whole-file rewrites for small edits	Rewrites the whole file rather than making a targeted edit; same result, more output tokens and time	Ask for targeted edits over whole-file rewrites

Unchanged from Fable 5

Adaptive thinking is always on: thinking: {"type": "enabled"} with budget_tokens and {"type": "disabled"} both return 400. Omit thinking or send {"type": "adaptive"}
thinking.display defaults to "omitted"; "summarized" is available, and the raw chain of thought is never returned
Prefilling the assistant response returns 400
Non-default temperature, top_p, or top_k values return 400
The minimum cacheable prompt length is still 512 tokens
Interleaved thinking is automatic, with no beta header

Refusals, Fallback, and Billing

Fable 5.1 carries safety classifiers covering the same stop_details categories as Fable 5:

Refusals: a declined request returns HTTP 200 with stop_reason: "refusal" and a stop_details object naming the policy area that fired
Fallback: retry a refused request on another model with server-side fallback. The permitted fallback targets for Fable 5.1 are Claude Opus 4.8 and Claude Opus 5
Billing: you aren’t billed for a refusal that arrives before any output, and fallback credit refunds the prompt-cache cost of switching models

Data Retention and Compliance (important)

Fable 5.1 and Mythos 5.1 still carry the 30-day data retention requirementBoth are Covered Models, the same as Fable 5 and Mythos 5: inputs and outputs are retained for 30 days for serious-abuse detection, and they aren’t available under zero data retention unless expressly authorized by Anthropic.

Default access scope: retained data is accessed only by automated safety systems; human review happens only when those systems flag potential harm
Human review scope: limited to what is needed to complete the review
Combined review across accounts: when traffic from multiple accounts is flagged for the same prohibited activity, it may be reviewed together

The retention happens at Anthropic and the cloud providers, not at APIYI: the 30-day retention above takes place provider-side (passed through to Anthropic for abuse detection). APIYI retains no data of its own and acts as a transparent proxy, forwarding requests only. Only Mythos-class models (Fable 5 / 5.1, Mythos 5 / 5.1) are subject to this requirement — other Claude models such as Opus 5, Opus 4.8, and Sonnet 5 are unaffected.

Putting It to Work

Where it fits

Long-horizon agentic coding: large cross-session refactors, migrations, multi-file feature work
Multistep research and deep retrieval: tasks that follow up on intermediate findings
Document-heavy knowledge work: filings, papers, chart-dense PDFs, through to a finished deliverable
Very long context analysis: connecting details across a 1M token window

Anthropic’s own guidance: start with Claude Opus 5 for most workloads. Reach for Fable 5.1 for demanding reasoning and long-horizon agentic work, or when your evals on Opus 5 at higher effort still fall short.

Code examples

Native Anthropic format

import anthropic

client = anthropic.Anthropic(
    api_key="your-apiyi-key",
    base_url="https://api.apiyi.com"
)

message = client.messages.create(
    model="claude-fable-5-1",
    max_tokens=8192,
    messages=[
        {
            "role": "user",
            "content": "Review this repository's architecture, flag the risks, and propose a refactor path. Batch independent tool calls into the same turn."
        }
    ]
)

print(message.content[0].text)

OpenAI-compatible format

from openai import OpenAI

client = OpenAI(
    api_key="your-apiyi-key",
    base_url="https://api.apiyi.com/v1"
)

response = client.chat.completions.create(
    model="claude-fable-5-1",
    messages=[
        {"role": "user", "content": "Trace the root cause of this production bug step by step and propose a fix."}
    ]
)

print(response.choices[0].message.content)

Five-step migration checklist

Change the model ID: claude-fable-5 → claude-fable-5-1
Remove forced tool use: drop tool_choice of type any / tool, and move schema enforcement to strict tool use or structured outputs
Keep history append-only: pass thinking blocks back unchanged, and don’t rebuild system / tools or edit earlier messages between requests
Re-tune effort: the default is high; consider changing it mid-conversation instead of holding one level for the whole session
Re-run your evals: refusal handling, fallback, and token counts carry over, but cache reads cost less and the default behaviors above differ

Pricing and Availability

Pricing

Official pricing (USD per 1M tokens):

Line item	Fable 5.1	Fable 5	Change
Base input	$10.00	$10.00	unchanged
Output	$50.00	$50.00	unchanged
5m cache writes	$12.50	$12.50	unchanged
1h cache writes	$20.00	$20.00	unchanged
Cache reads	$0.25	$1.00	down 75%

That table is also APIYI’s pricing — every line item matches the provider, with no markup. Cache reads (hits and refreshes) cost 0.025x the base input price on these models, versus 0.1x on other Claude models — the saving lands hardest on long agentic sessions that re-read the same cached prefix. Batch processing is $5 input / $25 output per 1M tokens.

APIYI prices this model in line with the provider and adds no markup. On top of that, some groups carry a discount and stack with recharge bonus campaigns — that part is our own margin given back, separate from the model’s pricing.For what you were actually charged, treat the console’s cache billing detail as authoritative — the usage cache fields echoed by the API are not a billing record.

Groups and endpoints

Item	Value
Model name	`claude-fable-5-1` (also `claude-fable-5-1-thinking`)
Groups	`default` / `svip` / `ClaudeCode`
OpenAI-compatible endpoint	`https://api.apiyi.com/v1`
Native Anthropic endpoint	`https://api.apiyi.com`

The ClaudeCode group is for clients speaking the native Anthropic protocol, such as Claude Code. Match the group to the protocol: use ClaudeCode for the native Anthropic protocol, and default / svip for the OpenAI-compatible protocol. That group also carries a discount, which stacks with recharge bonuses.

Stacking with recharge promotions

Pair this with APIYI’s recharge bonus campaigns to bring the effective cost down further: docs.apiyi.com/en/faq/recharge-promotions.

Verdict

Claude Fable 5.1 is an unusual release: the price of input and output doesn’t move at all, cache reads fall to a quarter, and the agentic benchmarks that matter most in production more than double. For teams already running long-horizon agents, the migration pays for itself quickly. On APIYI every line item matches the provider, cache reads included at the new $0.25. Confirm three things before you migrate:

Whether your code sets tool_choice to any or tool — it will 400 outright
Whether your conversation history is append-only — injected-then-deleted reminders and rebuilt system / tools arrays both invalidate thinking blocks
Whether your team knows about the 30-day data retention requirement, and handles sensitive data under your own compliance policy

Sources: Anthropic’s launch announcement and platform documentation (anthropic.com/claude-fable-and-mythos-5-1, platform.claude.com/docs/en/models/fable-5-1/whats-new-fable-5-1), released September 1, 2026. APIYI availability and pricing taken from the platform pricing endpoint; data retrieved September 2, 2026 (UTC+8). Final billing follows real-time platform data.

Changelog

AI Radar

Claude Fable 5.1 Is Live: Same Price, Cache Reads Cut to a Quarter

Key Takeaways

Background

What’s New

Capability gains

Long-horizon agentic coding

Documents, spreadsheets, slides

Research and search

Vision

Long context

Computer use

Benchmark highlights

Specifications

⚠️ Three Breaking Changes (read before migrating)

1. Forced tool use is not supported

2. Thinking blocks are tied to the model that produced them

3. Editing earlier turns invalidates thinking blocks

New Features (all beta)

Change effort mid-conversation

Turn-scoped system messages

Progress updates between tool calls

Behavior Differences from Fable 5 (no code change required to notice)

Unchanged from Fable 5

Refusals, Fallback, and Billing

Data Retention and Compliance (important)

Putting It to Work

Where it fits

Code examples

Native Anthropic format

OpenAI-compatible format

Five-step migration checklist

Pricing and Availability

Pricing

Groups and endpoints

Stacking with recharge promotions

Verdict

​Key Takeaways

​Background

​What’s New

​Capability gains

Long-horizon agentic coding

Documents, spreadsheets, slides

Research and search

Vision

Long context

Computer use

​Benchmark highlights

​Specifications

​⚠️ Three Breaking Changes (read before migrating)

​1. Forced tool use is not supported

​2. Thinking blocks are tied to the model that produced them

​3. Editing earlier turns invalidates thinking blocks

​New Features (all beta)

Change effort mid-conversation

Turn-scoped system messages

Progress updates between tool calls

​Behavior Differences from Fable 5 (no code change required to notice)

​Unchanged from Fable 5

​Refusals, Fallback, and Billing

​Data Retention and Compliance (important)

​Putting It to Work

​Where it fits

​Code examples

​Native Anthropic format

​OpenAI-compatible format

​Five-step migration checklist

​Pricing and Availability

​Pricing

​Groups and endpoints

​Stacking with recharge promotions

​Verdict

Key Takeaways

Background

What’s New

Capability gains

Benchmark highlights

Specifications

⚠️ Three Breaking Changes (read before migrating)

1. Forced tool use is not supported

2. Thinking blocks are tied to the model that produced them

3. Editing earlier turns invalidates thinking blocks

New Features (all beta)

Behavior Differences from Fable 5 (no code change required to notice)

Unchanged from Fable 5

Refusals, Fallback, and Billing

Data Retention and Compliance (important)

Putting It to Work

Where it fits

Code examples

Native Anthropic format

OpenAI-compatible format

Five-step migration checklist

Pricing and Availability

Pricing

Groups and endpoints

Stacking with recharge promotions

Verdict