Ministral 3 8B — Specifications
Compilado por Mustafa Ihsan de la documentación publicada por el proveedor · Última actualización
| Desarrollador | Mistral AI |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalidad | Texto, imagen → texto |
| Parámetros | 8.4B + 0.4B vision encoder |
| Ventana de contexto | 256K |
| Licencia | Apache 2.0 (abierta) |
| Pesos abiertos | Sí |
| Lanzado | 2025-12 |
| Precio de entrada | $0.15 /1M |
| Precio de salida | $0.15 /1M |
| Proveedores de API | Mistral API, Amazon Bedrock, OpenRouter, Ollama (local) |
Ejecútelo 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 y Qwen3 8B, and check what fits your GPU with the Calculadora de VRAM para LLM.
Ministral 3 8B pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $0.150 |
|---|---|
| Salida (por cada millón de tokens) | $0.150 |
| Relación salida/entrada | 1× |
| Combinada (4:1 entrada:salida) | $0.150 por 1 millón de tokens |
What Ministral 3 8B 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 | $0.19 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $3.75 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $38 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Ministral 3 8B
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Llama 3.1 8B abierta | $0.0240 | 84% cheaper |
| Mistral NeMo 12B abierta | $0.0292 | 81% más barato |
| Gemma 3 4B abierta | $0.0600 | 60% más económico |
¿Autoalojarlo o pagar por la 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 autohospedaje frente a API calcula el punto de equilibrio para su volumen de tokens.
Preguntas frecuentes
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.
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).