Claude Sonnet 4.6 — Especificaciones
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Desarrollador | Anthropic |
|---|---|
| Tipo | LLM |
| Modalidad | Texto y visión → texto |
| Parámetros | No revelado |
| Ventana de contexto | 1 millón |
| Salida máxima | 64 K |
| Licencia | Propietario |
| Pesos abiertos | No |
| Lanzado | 2025 |
| Precio de entrada | $3.00 /1M |
| Precio de salida | $15.00 /1M |
| Proveedores de 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
| Entrada (por cada millón de tokens) | $3.00 |
|---|---|
| Salida (por cada millón de tokens) | $15.00 |
| Relación salida/entrada | 5× |
| Combinada (4:1 entrada:salida) | $5.40 por 1 millón de tokens |
What Claude Sonnet 4.6 costs per month
Gasto mensual real con una mezcla entrada:salida de 4:1, es decir, la proporción que realmente genera una carga de trabajo típica de chat o RAG.
| Carga de trabajo | Tokens/mes | Coste mensual |
|---|---|---|
| Proyecto secundario | 1 millón de tokens de entrada / 0,25 millones de tokens de salida | $6.75 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $135 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $1,350 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Claude Sonnet 4.6
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| GLM 5.2 abierta | $2.00 | 63 % más barato |
| Gemini 3.5 Flash | $3.00 | 44 % más barato |
| Gemini 3.1 Pro | $4.00 | 26 % más barato |
Preguntas frecuentes
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.
Vea todos los modelos Claude comparados lado a lado: Precios de la API de Claude.
Los precios corresponden a las tarifas oficiales publicadas para la API principal del modelo y se revisan periódicamente conforme los proveedores los actualicen. No incluyen descuentos por volumen, procesamiento por lotes ni entradas en caché. Compare todos los modelos uno al lado del otro en la Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).