Ministral 3 8B — Specifications
Compilado por Mustafa Ihsan da documentação publicada pelo fornecedor · Última atualização
| Desenvolvedor | Mistral AI |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalidade | Texto, Imagem → Texto |
| Parâmetros | 8.4B + 0.4B vision encoder |
| Janela de contexto | 256K |
| Licença | Apache 2.0 (aberta) |
| Pesos abertos | Sim |
| Lançado | 2025-12 |
| Preço da entrada | $0.15 /1M |
| Preço da saída | $0.15 /1M |
| Provedores de API | Mistral API, Amazon Bedrock, OpenRouter, Ollama (local) |
Execute-o localmente
| VRAM (4 bits) | ~8 GB |
|---|
What is Ministral 3 8B?
Ministral 3 8B is the middle model of Mistral AI’s Ministral 3 family, released on 2 December 2025 alongside Mistral Large 3 under the Apache 2.0 licence. It pairs an 8.4B language model with a 0.4B vision encoder, so it reads images as well as text, and it has a 256K-token context window. Mistral built the family for edge and local use and ships base, instruct and reasoning versions (per Mistral’s launch post).
On Mistral’s API (ministral-8b-2512) it costs $0.15 per million input tokens and $0.15 per million output tokens, with cached input at $0.015 (per Mistral’s pricing page). Amazon Bedrock and OpenRouter also carry it. For local use, Mistral’s model page puts the approximate minimum at 8 GB of GPU memory for 4-bit weights with a 16K context, 17 GB at 4-bit with a quarter of the full context, and 67 GB for BF16 at the full 256K. Mistral’s own GGUF release has a 5.2 GB Q4_K_M file plus a 0.86 GB vision projector, and Ollama’s default ministral-3:8b build is a 6.0 GB download.
Mistral names it the replacement for both Mistral 7B (retired from Mistral’s API on 30 March 2025) and Mistral NeMo 12B (retired on 31 July 2026). Compared with Mistral 7B it adds image input and a 256K window instead of 32K. For other 8B-class options see Llama 3.1 8B e Qwen3 8B, and check what fits your GPU with the Calculadora de VRAM para LLMs.
Ministral 3 8B pricing: API cost per 1M tokens
| Entrada (por 1 milhão de tokens) | $0.150 |
|---|---|
| Saída (por 1 milhão de tokens) | $0.150 |
| Razão saída/entrada | 1× |
| Misturada (4:1 entrada:saída) | $0.150 por 1 milhão de tokens |
What Ministral 3 8B 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 | $0.19 |
| Equipe pequena | 20 milhões de tokens de entrada / 5 milhões de tokens de saída | $3.75 |
| Produção | 200 milhões de tokens de entrada / 50 milhões de tokens de saída | $38 |
Calcule seus próprios números na Calculadora de custos de API de IA.
Cheaper alternatives to Ministral 3 8B
| Modelo | Custo médio ponderado por US$ 1 milhão | Você economiza |
|---|---|---|
| Llama 3.1 8B aberta | $0.0240 | 84% cheaper |
| Mistral NeMo 12B aberta | $0.0292 | 81% mais barato |
| Gemma 3 4B aberta | $0.0600 | 60% mais barato |
Hospedar localmente ou pagar pela API?
Ministral 3 8B is open-weight, so you can run it yourself. It needs ~8 GB of VRAM at 4-bit. Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calculadora de self-hosting vs API calcula o ponto de equilíbrio para seu volume de tokens.
Perguntas frequentes
How much does Ministral 3 8B cost per 1M tokens?
Ministral 3 8B costs $0.150 per 1M input tokens and $0.150 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.150 per 1M tokens.
How much does Ministral 3 8B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $3.75 on Ministral 3 8B. A side project (1M in / 0.25M out) costs roughly $0.19.
What is a cheaper alternative to Ministral 3 8B?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 84% less than Ministral 3 8B. It is also open-weight, so self-hosting is an option.
Can I run Ministral 3 8B locally?
Yes. Ministral 3 8B is open-weight and needs about ~8 GB of VRAM at 4-bit quantisation.
Why does Ministral 3 8B 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. Ministral 3 8B charges 1× 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.