Claude Opus 4.8 — Specifiche
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Sviluppatore | Anthropic |
|---|---|
| Tipo | LLM (ragionamento) |
| Modalità | Testo, visione → testo |
| Parametri | Non divulgato |
| Finestra contestuale | 1 milione |
| Output massimo | 128K |
| Licenza | Proprietaria |
| Pesi aperti | No |
| Pubblicato | 2026 |
| Prezzo dell’input | $5.00 /1M |
| Prezzo dell’output | $25.00 /1M |
| Provider API | Anthropic, AWS, Vertex AI, Azure |
What is Claude Opus 4.8?
Claude Opus 4.8 is Anthropic’s Opus-tier flagship for state-of-the-art long-horizon
agentic work, coding and knowledge tasks. It runs adaptive thinking only, and carries a
1M-token context window at standard pricing — there is no long-context premium, which
distinguishes it from several rivals that step the input rate up once a prompt passes a
threshold. At $5 in / $25 out per million tokens it sits squarely in the frontier bracket.
The no-premium 1M context is the practical reason to choose it. Models that double their
input rate above 200K tokens make large-context work unpredictable to budget: the same
feature costs a different amount depending on how much a user pasted in. Opus 4.8 bills the
same rate from the first token to the millionth, so a retrieval-heavy application can size
its prompts around what produces the best answer rather than around a pricing cliff. It has
since been joined by Claude Opus 5, which ranks higher on the Artificial Analysis
Intelligence Index at identical pricing — so for new builds, check whether Opus 5 is
available in your region and provider before defaulting to 4.8.
Claude Opus 4.8 pricing: API cost per 1M tokens
| Input (per ogni milione di token) | $5.00 |
|---|---|
| Output (per ogni milione di token) | $25.00 |
| Rapporto output/input | 5× |
| Combinato (4:1 in:out) | $9.00 per 1 milione di token |
What Claude Opus 4.8 costs per month
Spesa mensile reale con un mix input-to-output 4:1 — il rapporto effettivamente prodotto da un tipico carico di lavoro basato su chat o RAG.
| Carico di lavoro | Token/mese | Costo/mese |
|---|---|---|
| Progetto secondario | 1 milione in ingresso / 0,25 milioni in uscita | $11 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $225 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $2,250 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Cheaper alternatives to Claude Opus 4.8
| Modello | Costo combinato ($/1 milione) | Risparmi |
|---|---|---|
| Kimi K3 aperta | $5.40 | 40% più economico |
| GLM 5.2 aperta | $2.00 | 78% più economico |
| Gemini 3.5 Flash | $3.00 | 67% più economico |
Domande frequenti
How much does Claude Opus 4.8 cost per 1M tokens?
Claude Opus 4.8 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $9.00 per 1M tokens.
How much does Claude Opus 4.8 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $225 on Claude Opus 4.8. A side project (1M in / 0.25M out) costs roughly $11.25.
What is a cheaper alternative to Claude Opus 4.8?
Kimi K3 is the strongest cheaper option in our database at $5.40 per 1M blended — about 40% less than Claude Opus 4.8. It is also open-weight, so self-hosting is an option.
Can I run Claude Opus 4.8 locally?
No. Claude Opus 4.8 is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Claude Opus 4.8 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 Opus 4.8 charges 5× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Visualizza tutti i modelli Claude confrontati fianco a fianco: Prezzi API Claude.
I prezzi indicati sono le tariffe ufficiali pubblicate per l'API principale del modello e vengono aggiornati man mano che i fornitori li modificano. Sconti per volumi elevati, elaborazione batch e input memorizzati nella cache non sono inclusi. Confronta tutti i modelli fianco a fianco nel Database di modelli IA o il Classifica LLM.