Claude Sonnet 4.6 — Specifiche
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Sviluppatore | Anthropic |
|---|---|
| Tipo | LLM |
| Modalità | Testo, visione → testo |
| Parametri | Non divulgato |
| Finestra contestuale | 1 milione |
| Output massimo | 64K |
| Licenza | Proprietaria |
| Pesi aperti | No |
| Pubblicato | 2025 |
| Prezzo dell’input | $3.00 /1M |
| Prezzo dell’output | $15.00 /1M |
| Provider API | Anthropic, AWS, Vertex AI, Azure |
What is Claude Sonnet 4.6?
Claude Sonnet 4.6 is Anthropic’s balance point between speed and intelligence: adaptive
thinking, a 1M-token context window, 64K maximum output, and pricing of $3 in / $15 out per
million tokens. It is the default workhorse for most production workloads, and the tier most
teams land on after discovering that Opus is overkill for the majority of their traffic and
Haiku is underpowered for the rest.
What makes Sonnet the pragmatic pick is that it gives up very little at the top of the
range while costing 40% less than Opus 4.8 on both input and output. The 1M context is
identical, adaptive thinking is identical, and the gap only becomes visible on genuinely
hard multi-step reasoning. For retrieval-augmented generation, code review, structured
extraction over long documents and customer-facing assistants, that gap rarely shows up in
output quality but always shows up on the invoice. Note that Claude Sonnet 5 now sits below
it on price — $2 / $10 during its introductory period — so a new project should compare the
two directly before committing to 4.6.
Claude Sonnet 4.6 pricing: API cost per 1M tokens
| Input (per ogni milione di token) | $3.00 |
|---|---|
| Output (per ogni milione di token) | $15.00 |
| Rapporto output/input | 5× |
| Combinato (4:1 in:out) | $5.40 per 1 milione di token |
What Claude Sonnet 4.6 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 | $6.75 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $135 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $1,350 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Cheaper alternatives to Claude Sonnet 4.6
| Modello | Costo combinato ($/1 milione) | Risparmi |
|---|---|---|
| GLM 5.2 aperta | $2.00 | 63% più economico |
| Gemini 3.5 Flash | $3.00 | 44% più economico |
| Gemini 3.1 Pro | $4.00 | 26% più economico |
Domande frequenti
How much does Claude Sonnet 4.6 cost per 1M tokens?
Claude Sonnet 4.6 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $5.40 per 1M tokens.
How much does Claude Sonnet 4.6 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $135 on Claude Sonnet 4.6. A side project (1M in / 0.25M out) costs roughly $6.75.
What is a cheaper alternative to Claude Sonnet 4.6?
GLM 5.2 is the strongest cheaper option in our database at $2.00 per 1M blended — about 63% less than Claude Sonnet 4.6. It is also open-weight, so self-hosting is an option.
Can I run Claude Sonnet 4.6 locally?
No. Claude Sonnet 4.6 is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Claude Sonnet 4.6 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 Sonnet 4.6 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.