Claude Fable 5 — Spezifikationen
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Entwickler | Anthropic |
|---|---|
| Typ | LLM (Spitzenleistung bei Schlussfolgerungen) |
| Modality | Text, Vision → Text |
| Parameter | Nicht offengelegt |
| Kontextfenster | 1 Mio. |
| Maximale Ausgabe | 128 K |
| Lizenz | Proprietär |
| Offene Gewichte | Nein |
| Veröffentlicht | 2026 |
| Eingabepreis | $10.00 /1M |
| Ausgabepreis | $50.00 /1M |
| API-Anbieter | Anthropic, AWS |
What is Claude Fable 5?
Claude Fable 5 is Anthropic’s most capable widely released model, positioned above the
Opus tier and priced accordingly at $10 in / $50 out per million tokens. Thinking is always
on — there is no non-reasoning mode to fall back to — which is what makes it strong on
long-horizon agentic work and what makes it expensive on anything trivial. It pairs a
1M-token context window with a 128K maximum output, an unusually large generation budget
that matters when the task is producing a long artifact rather than answering a question.
The economics only work at the top of the difficulty curve. At $50 per million output
tokens, Fable 5 costs roughly five times Claude Opus 4.8 on the output side, so routing
ordinary requests to it burns budget for no measurable gain. The sensible pattern is a
router: Fable 5 for the small share of tasks where a wrong answer is expensive — multi-step
agents that run unattended, deep research, refactors across a large codebase — and a
Sonnet- or Haiku-tier model for everything else. If your workload is mostly retrieval and
summarisation, the price gap will dominate your bill long before capability does.
Claude Fable 5 pricing: API cost per 1M tokens
| Eingabe (pro 1 Mio. Token) | $10.00 |
|---|---|
| Ausgabe (pro 1 Mio. Token) | $50.00 |
| Verhältnis Output/Input | 5× |
| Gemischt (4:1 Input:Output) | $18.00 pro 1 Mio. Tokens |
What Claude Fable 5 costs per month
Tatsächliche monatliche Ausgaben bei einem 4:1-Input-zu-Output-Mix – dem Verhältnis, das typische Chat- oder RAG-Arbeitslasten tatsächlich erzeugen.
| Workload | Tokens/Monat | Kosten pro Monat |
|---|---|---|
| Nebenprojekt | 1 Mio. Eingabe / 0,25 Mio. Ausgabe | $23 |
| Kleines Team | 20 Mio. Eingabe / 5 Mio. Ausgabe | $450 |
| Produktion | 200 Mio. Eingabe / 50 Mio. Ausgabe | $4,500 |
Stellen Sie Ihre eigenen Berechnungen im KI-API-Kostenrechner.
Cheaper alternatives to Claude Fable 5
| Modell | Gewichteter Preis pro Million US-Dollar | Sie sparen |
|---|---|---|
| Claude Opus 5 | $9.00 | 50% cheaper |
| GPT-5.6 Sol | $10.00 | 44 % günstiger |
| Kimi K3 offenere | $5.40 | 70% cheaper |
Häufig gestellte Fragen
How much does Claude Fable 5 cost per 1M tokens?
Claude Fable 5 costs $10.00 per 1M input tokens and $50.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $18.00 per 1M tokens.
How much does Claude Fable 5 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $450 on Claude Fable 5. A side project (1M in / 0.25M out) costs roughly $22.50.
What is a cheaper alternative to Claude Fable 5?
Claude Opus 5 is the strongest cheaper option in our database at $9.00 per 1M blended — about 50% less than Claude Fable 5.
Can I run Claude Fable 5 locally?
No. Claude Fable 5 is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Claude Fable 5 charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Claude Fable 5 charges 5× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Alle Claude-Modelle im direkten Preisvergleich: Claude-API-Preise.
Die Preise entsprechen den offiziell veröffentlichten Listenpreisen für die primäre API des jeweiligen Modells und werden regelmäßig aktualisiert, sobald Anbieter diese ändern. Volumen-, Batch- und Cached-Input-Rabatte sind nicht enthalten. Vergleichen Sie alle Modelle nebeneinander im Datenbank für KI-Modelle oder das LLM-Leaderboard.