Muse Spark 1.3 — Specifications
Compilado por Mustafa Ihsan da documentação publicada pelo fornecedor · Última atualização
| Desenvolvedor | Meta |
|---|---|
| Tipo | Raciocínio / agente |
| Modalidade | Text, image, video, audio, PDF → Text |
| Parâmetros | Não divulgado |
| Janela de contexto | 1 milhão |
| Licença | Proprietário |
| Pesos abertos | Não |
| Lançado | 2026-09 |
| Preço da entrada | $1.25 /1M |
| Preço da saída | $4.25 /1M |
| Provedores 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. o anúncio da 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 custos de API de IA.
Muse Spark 1.3 pricing: API cost per 1M tokens
| Entrada (por 1 milhão de tokens) | $1.25 |
|---|---|
| Saída (por 1 milhão de tokens) | $4.25 |
| Razão saída/entrada | 3.4× |
| Misturada (4:1 entrada:saída) | $1.85 por 1 milhão de tokens |
What Muse Spark 1.3 costs per month
Gasto mensal real com uma proporção de entrada para saída de 4:1 — a razão efetivamente gerada por cargas de trabalho típicas de chat ou RAG.
| Carga de trabalho | Tokens/mês | Custo por mês |
|---|---|---|
| Projeto paralelo | 1 milhão de tokens de entrada / 0,25 milhão de tokens de saída | $2.31 |
| Equipe pequena | 20 milhões de tokens de entrada / 5 milhões de tokens de saída | $46 |
| Produção | 200 milhões de tokens de entrada / 50 milhões de tokens de saída | $463 |
Calcule seus próprios números na Calculadora de custos de API de IA.
Cheaper alternatives to Muse Spark 1.3
| Modelo | Custo médio ponderado por US$ 1 milhão | Você economiza |
|---|---|---|
| Llama 3.1 8B aberta | $0.0240 | 99% mais barato |
| Mistral NeMo 12B aberta | $0.0292 | 98% cheaper |
| Gemma 3 4B aberta | $0.0600 | 97% mais barato |
Perguntas frequentes
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.
Os preços correspondem às tarifas listadas oficialmente para a API principal do modelo e são revisados conforme os provedores os atualizam. Descontos por volume, processamento em lote ou entradas em cache não estão incluídos. Compare todos os modelos lado a lado na Banco de dados de modelos de IA ou o Ranking de LLMs.