Muse Spark 1.3 — Specifications
Compilado por Mustafa Ihsan de la documentación publicada por el proveedor · Última actualización
| Desarrollador | Meta |
|---|---|
| Tipo | Razonamiento / agente |
| Modalidad | Text, image, video, audio, PDF → Text |
| Parámetros | No revelado |
| Ventana de contexto | 1 millón |
| Licencia | Propietario |
| Pesos abiertos | No |
| Lanzado | 2026-09 |
| Precio de entrada | $1.25 /1M |
| Precio de salida | $4.25 /1M |
| Proveedores de API | Meta Model API (also in Muse Code) |
What is Muse Spark 1.3?
Muse Spark 1.3 is Meta’s model for agentic and coding work at scale, released on 2 September 2026 on Meta Model API and in Muse Code. el anuncio de Meta says it sustains long, multi-step work better than earlier Muse Spark models, and that in comparisons by Meta engineers it used about 20% fewer tool calls and 25% fewer tokens than Muse Spark 1.2. It accepts text, images, video, audio and PDF, returns text, has a 1,048,576-token context window and supports reasoning effort from minimal to max (default high). Meta’s docs recommend it for new work but warn that audio understanding on 1.3 is not fully supported; use Muse Spark 1.2 for audio.
In Standard mode it costs $1.25 per million input tokens, $0.15 for cached input and $4.25 per million output tokens, with no long-context premium. Contributor mode (muse-spark-1.3-contributor) drops that to $0.10, $0.002 and $0.20, but Meta may then use your prompts, code, files and the model’s responses to train future Meta models, and the max reasoning level is not available. Web search grounding adds $2.50 per 1,000 queries (see Meta’s pricing page).
Muse Spark sits in the middle of Meta’s lineup: Muse Wonder ($4 / $20, in preview) is Meta’s most capable model, and Muse Ember ($0.10 / $0.50 for requests up to 200K input tokens) handles high-volume sub-tasks. Muse Spark Open is a separate open-weight release (816B total, 42B active parameters); Muse Spark 1.3 itself is a hosted model without public weights. Meta’s Model API lists no Llama models, so for open Llama weights see Llama 4 Maverick, and compare monthly costs with the Calculadora de costos de API de IA.
Muse Spark 1.3 pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $1.25 |
|---|---|
| Salida (por cada millón de tokens) | $4.25 |
| Relación salida/entrada | 3.4× |
| Combinada (4:1 entrada:salida) | $1.85 por 1 millón de tokens |
What Muse Spark 1.3 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 | $2.31 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $46 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $463 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Muse Spark 1.3
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Llama 3.1 8B abierta | $0.0240 | 99 % más barato |
| Mistral NeMo 12B abierta | $0.0292 | 98% cheaper |
| Gemma 3 4B abierta | $0.0600 | 97% más barato |
Preguntas frecuentes
How much does Muse Spark 1.3 cost per 1M tokens?
Muse Spark 1.3 costs $1.25 per 1M input tokens and $4.25 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $1.85 per 1M tokens.
How much does Muse Spark 1.3 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $46 on Muse Spark 1.3. A side project (1M in / 0.25M out) costs roughly $2.31.
What is a cheaper alternative to Muse Spark 1.3?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 99% less than Muse Spark 1.3. It is also open-weight, so self-hosting is an option.
Can I run Muse Spark 1.3 locally?
No. Muse Spark 1.3 is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Muse Spark 1.3 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. Muse Spark 1.3 charges 3.4× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
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).