# Claude Fable 5 is free for 4 more days. Here is the full guide > Source: > Published: 2026-07-08 08:50:15+00:00 # Claude Fable 5 is free for 4 more days. Here is the full guide ### Anthropic’s strongest model ever is included in paid plans until July 12. The best practices, the copy-paste prompts, and the two patterns that keep 90%+ of its power once the bill starts. Anthropic shipped its most intelligent model ever, a government switched it off, and now it is free for everyone on a paid plan. *Until Sunday.* **Claude Fable 5** is the first model in the new Mythos class, a tier above Opus. It is included on Pro, Max, and Team plans through **July 12 at 11:59 PM PT**, up to half your weekly limit. After that, it moves to usage credits at **$10 per million input tokens and $50 per million output**, double [Opus 4.8](https://www.the-ai-corner.com/t/claude-and-anthropic?r=1krivi). Simon Willison called it “something of a beast” and said “the challenge is finding tasks that it can’t do.” He also burned $110 of API credit in a day, which tells you why this guide has two halves: how to use the free window, and how to keep the power once it costs money. I read the docs, the [prompting guide](https://www.the-ai-corner.com/t/prompting-and-context-engineering?r=1krivi), and the cookbooks so you can skip them. Here is everything, free. ## What Fable 5 actually is ▫️ **A tier jump, over an increment.** On SWE-bench Pro it scores **80.3%**, with Opus 4.8 at 69.2% and GPT-5.5 at 58.6%. On SWE-bench Verified it holds the **#1 slot near 95%**. On Terminal-Bench, 88%. The lead grows as tasks get longer and harder, which is the whole point of the Mythos class: built for [agentic](https://www.the-ai-corner.com/t/ai-agents?r=1krivi), long-horizon work with low error compounding. ▫️ **1M-token context, 128K output, zero long-context surcharge.** A 900K-token request bills at the same per-token rate as a 9K one. Feed it the whole [data room](https://www.thevccorner.com/t/investor-lists?sort=top), the whole codebase, the whole contract stack. ▫️ **The same model as Mythos 5, with guardrails.** Mythos 5 runs unblocked for vetted organizations; Fable 5 ships with safety classifiers. That difference is why a US export order [switched both off worldwide on June 12](https://www.the-ai-corner.com/p/anthropic-fable-5-mythos-5-government-ban-2026?r=1krivi), the first frontier model shut down by regulators, before returning July 1 with a stronger classifier. Around 1 in 20 sessions gets silently rerouted to Opus 4.8 when the classifier fires, worth knowing before you blame your prompt. ▫️ **The proof is public.** Stripe ran a codebase-wide migration inside a 50-million-line Ruby codebase in one day, work scoped at two months for a team. One builder had it hand-code a GPU kernel in 2.5 hours for an 18.7x speedup. Andrej Karpathy called a community demo “incredible.” ## How to prompt it (this part changed) Fable 5 punishes Opus-era habits. Anthropic’s own guide frames everything as a delta, and the [best-practices playbook](https://www.the-ai-corner.com/p/claude-best-practices-power-user-guide-2026?r=1krivi) needs three updates: **Describe the outcome, skip the steps.** Instruction-following is now strong enough that step-lists become handcuffs the model obeys even when they hurt. Old CLAUDE.md files full of “always do X before Y” now work against you. Rewrite them.**Thinking is always on, and you steer with effort.** There is zero off switch, temperature is gone, and asking it to “show your reasoning step by step” can trigger a refusal category. Set`/effort` instead: high by default, xhigh for the hardest work, low for routine. Lower effort on Fable 5 often beats max effort on older models.**Front-load everything.** It skips clarifying questions by default. Give it the goal, the audience, the constraints, and the definition of done in message one, the core move of[context engineering](https://www.the-ai-corner.com/p/context-engineering-guide-2026?r=1krivi). My favorite framing from the official guide: “I’m working on [X] for [who]. They need [what it enables]. With that in mind: [request].” Four more copy-paste lines that earn their place in every long run: “Before reporting progress, audit each claim against a tool result from this session.” That one nearly eliminated fabricated status reports in Anthropic’s testing, the failure the [reliability playbook](https://www.the-ai-corner.com/p/ai-agent-reliability-playbook?r=1krivi) exists for. “When the user is describing a problem or thinking out loud rather than requesting a change, the deliverable is your assessment. Report findings and stop.” “When you have enough information to act, act. Give a recommendation, rather than an exhaustive survey.” “Don’t add features, refactor, or introduce abstractions beyond what the task requires.” Boundaries, decisiveness, and restraint: the three behaviors a stronger model needs spelled out. ## What to run during the free window Four days. Spend them on work where a wrong answer is expensive, since that is where the tier jump pays: ▫️ **The refactor you have postponed.** Multi-file, cross-cutting, the one that scares you. In [Claude Code](https://www.the-ai-corner.com/p/the-claude-code-system-that-replaces?r=1krivi), switch with `/model fable` (v2.1.170+), and pair it with a [/goal loop](https://www.the-ai-corner.com/p/claude-code-loops-library-goal-schedule-recipes-2026?r=1krivi) so it grinds until tests pass. ▫️ **Whole-document analysis.** A contract plus its exhibits, an earnings narrative against its own tables, a full [competitor teardown](https://www.thevccorner.com/p/what-top-vcs-look-for-2026-founder-playbook?r=1krivi). The 1M window is the feature. ▫️ **A head-to-head test.** Same hard task, two chats, Fable 5 versus Opus 4.8. You learn in twenty minutes whether the delta matters for *your* work, before you ever pay for it. ▫️ **Durable assets over one-off outputs.** Have it write reusable Skills, a memory file, a CLAUDE.md audit, or your [agent architecture](https://www.the-ai-corner.com/p/how-to-build-ai-agent-guide-2026?r=1krivi). Outputs you keep after the window closes. ▫️ **An overnight run.** The Mythos class was built for long-horizon autonomy, the pattern behind the [Autoresearch Playbook](https://www.the-ai-corner.com/p/autoresearch-playbook-agent-optimization-loops-2026?r=1krivi) and every serious [loop](https://www.the-ai-corner.com/p/loop-engineering-coding-agents-2026?r=1krivi). Skip it for quick emails and simple lookups. It is slower to first token and counts roughly double against your usage limits, so routine work stays on Sonnet. ## The two patterns that keep the power after July 12 Here is the part most people will miss, and it comes straight from Anthropic’s own numbers. You keep 90%+ of Fable 5 while paying half or less, by changing *where* it sits in your stack. **Pattern 1: Fable 5 as the advisor.** A cheaper executor (Sonnet 5) does the work and calls Fable 5 for guidance when stuck, about once per task.On SWE-bench Pro, this combo hits **~92% of Fable 5’s score at ~63% of the price**, because most tokens bill at the executor’s rate. It ships as a first-class advisor tool in the API, and the pattern generalizes: the expensive brain steers, the cheap hands type.**Pattern 2: Fable 5 as the orchestrator.** Flip it. Fable 5 plans and delegates to Sonnet 5 workers through[Claude Managed Agents](https://www.the-ai-corner.com/p/claude-managed-agents-guide-2026?r=1krivi), and the token-heavy grunt work bills at the worker rate.On BrowseComp, this hits **96% of Fable 5’s performance at 46% of the cost**. Anthropic’s own cookbook example makes it concrete: verifying 20 facts across the largest US national parks cost**$1.61 in 194 seconds** with the split team, versus**$4.00 and 608 seconds** for Fable 5 alone. Cheaper*and*three times faster. The rule of thumb: **advisor** for coding and agent tasks where a cheap model owns the workload, **orchestrator** for research and fan-out where the win is keeping bulk tokens away from the expensive model. Both stack with prompt caching (cache reads at a tenth of the input rate) and the Batch API (50% off), the levers from the [token-cost playbook](https://www.the-ai-corner.com/p/llm-token-cost-optimization-playbook-2026?r=1krivi). One warning for Claude Code users: subagents inherit the session model by default. A Fable 5 session with an unpinned subagent fleet bills *everything* at Fable rates. Pin your workers (`model: sonnet` or `haiku` ) before you walk away. ## The bigger picture Anthropic is running the classic land-and-price play: give everyone a taste of the frontier, then charge for it, the same ladder logic as every [pricing journey](https://www.thevccorner.com/p/the-startup-pricing-journey?r=1krivi). And it is working. Anthropic already [passed OpenAI in enterprise API revenue](https://www.the-ai-corner.com/p/anthropic-30b-arr-passed-openai-revenue-2026?r=1krivi), the Mythos tier gives it a premium shelf, and the free window is the demand test, in a quarter where [capital keeps flooding the AI build](https://www.thevccorner.com/p/q1-2026-us-fund-activity-record-fundraising?r=1krivi). For you, the play is simpler. Test it on your hardest work this week while it costs zero. Decide with your own evidence whether the tier jump moves *your* metric. And if it does, run it as an advisor or an orchestrator rather than a default, because the [one-person operations](https://www.the-ai-corner.com/p/one-person-startup-operating-system-2026?r=1krivi) that win this era route intelligence like a resource, exactly the discipline behind all [100 agent ideas worth building](https://www.thevccorner.com/p/100-ai-agent-ideas-implementation-guide?r=1krivi). Four days. The frontier is on the house. ## TL;DR Claude Fable 5, the first Mythos-class model above Opus, is included on paid plans through July 12 at 11:59 PM PT, then moves to credits at $10/$50 per million tokens. It leads SWE-bench Pro at 80.3% (Opus 4.8: 69.2%, GPT-5.5: 58.6%) with a 1M context window and 128K output. Prompt it differently: outcomes over step-lists, effort levels instead of temperature, full context up front, and the four copy-paste lines above for long runs. Spend the free window on hard, expensive-if-wrong work: the postponed refactor, whole-document analysis, an overnight loop, a head-to-head against Opus. After July 12, keep 90%+ of the power for half the price: Sonnet 5 executor with a Fable 5 advisor (~92% of the score at ~63% of the cost) or a Fable 5 orchestrator with Sonnet 5 workers (96% at 46%). Pin your subagent models, cache aggressively, and route intelligence like a resource. ## Keep reading #### Master Claude ▫️ [Claude best practices: the power-user guide](https://www.the-ai-corner.com/p/claude-best-practices-power-user-guide-2026?r=1krivi) ▫️ [The context engineering guide](https://www.the-ai-corner.com/p/context-engineering-guide-2026?r=1krivi) ▫️ [The Loop Library: 12 Claude Code loop recipes](https://www.the-ai-corner.com/p/claude-code-loops-library-goal-schedule-recipes-2026?r=1krivi) #### Build with agents ▫️ [The Claude managed agents guide](https://www.the-ai-corner.com/p/claude-managed-agents-guide-2026?r=1krivi) ▫️ [The AI agent reliability playbook](https://www.the-ai-corner.com/p/ai-agent-reliability-playbook?r=1krivi) ▫️ [The token-cost optimization playbook](https://www.the-ai-corner.com/p/llm-token-cost-optimization-playbook-2026?r=1krivi) #### The business of AI ▫️ [Anthropic passed OpenAI at $30B ARR](https://www.the-ai-corner.com/p/anthropic-30b-arr-passed-openai-revenue-2026?r=1krivi)