Anthropic Claude Fable 5
Anthropic's Claude 5-family model for the most demanding reasoning, coding, and agentic work — with vision and a 128K output budget.
Claude Fable 5 is a cloud text model from Anthropic. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1M input tokens and up to 128K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions. It runs through Runware and Replicate using your own API key, from $10.00 per million input tokens.
- Released
- 3 months ago (Jun 2026)
- Pricing
- $10.00 / 1M in · $50.00 / 1M out
- Inputs
- Text, Images
- Context window
- 1M in · 128K out
- Reasoning
- Adjustable effort
- Controls
- System prompt
Examples
Generated with Claude Fable 5 via Runware. The same three prompts run against every text model in the catalog, shown verbatim — so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a set of rules that lets one computer program request information or actions from another. Think of a power outlet: you don't need to understand the electrical grid, you just plug in using a standard interface, and electricity arrives. APIs work the same way for software.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
Use a hosted provider. With two people, every hour spent on authentication is an hour not spent on the product that actually differentiates you. Auth is deceptively hard to get right: password hashing, session management, token rotation, account recovery, rate limiting, and breach response are all places where a small mistake becomes a catastrophic security incident that could kill a young company's reputation. Services like Auth0, Clerk, or Supabase Auth give you battle-tested security, social logins, and MFA in an afternoon, usually free at your current scale. The strongest argument against this: vendor lock-in combined with pricing that scales per-user. Hosted auth is cheap until it suddenly isn't, and migrating thousands of user credentials off a provider later is painful and risky, sometimes requiring forced password resets. If you succeed, you may face a steep bill or a miserable migration at exactly the moment you're scaling fastest.
Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.
Your AI spending is hard to predict for three main reasons. First, most AI services charge by usage rather than a flat fee. Costs depend on how much text employees send and receive, and a single complex request can cost many times more than a simple one. Second, the market itself is unstable. Vendors change prices, release new models, and retire old ones frequently, so a budget built on today's rates can be obsolete within months. Third, adoption inside the company is unpredictable. Teams experiment, usage spreads informally, and a pilot that succeeds can multiply consumption overnight without anyone approving new spending. So what can you do about it? Require every AI project to have an owner accountable for its costs. Set spending alerts and hard caps with vendors so surprises surface in days, not at quarter end. Negotiate committed-use discounts or fixed-price tiers once usage stabilizes. Centralize purchasing so you see all AI spending in one place, including tools bought on credit cards. Finally, treat AI budgets as ranges rather than fixed numbers, reviewed monthly, and fund a contingency reserve. You cannot eliminate the uncertainty, but you can shorten the time between a cost spike and your awareness of it, which is what matters.
Anthropic
Anthropic builds the Claude family of large language models, focused on safety, helpfulness, and honesty.
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