Ministral 3 8B — Specifications
Compilato da Mustafa Ihsan dalla documentazione pubblicata del fornitore · Ultimo aggiornamento
| Sviluppatore | Mistral AI |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalità | Testo, immagine → testo |
| Parametri | 8.4B + 0.4B vision encoder |
| Finestra contestuale | 256K |
| Licenza | Apache 2.0 (open) |
| Pesi aperti | Sì |
| Pubblicato | 2025-12 |
| Prezzo dell’input | $0.15 /1M |
| Prezzo dell’output | $0.15 /1M |
| Provider API | Mistral API, Amazon Bedrock, OpenRouter, Ollama (local) |
Esegui localmente
| VRAM (4-bit) | ~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 Calcolatore VRAM per LLM.
Ministral 3 8B pricing: API cost per 1M tokens
| Input (per ogni milione di token) | $0.150 |
|---|---|
| Output (per ogni milione di token) | $0.150 |
| Rapporto output/input | 1× |
| Combinato (4:1 in:out) | $0.150 per 1 milione di token |
What Ministral 3 8B costs per month
Spesa mensile reale con un mix input-to-output 4:1 — il rapporto effettivamente prodotto da un tipico carico di lavoro basato su chat o RAG.
| Carico di lavoro | Token/mese | Costo/mese |
|---|---|---|
| Progetto secondario | 1 milione in ingresso / 0,25 milioni in uscita | $0.19 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $3.75 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $38 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Cheaper alternatives to Ministral 3 8B
| Modello | Costo combinato ($/1 milione) | Risparmi |
|---|---|---|
| Llama 3.1 8B aperta | $0.0240 | 84% cheaper |
| Mistral NeMo 12B aperta | $0.0292 | 81% più economico |
| Gemma 3 4B aperta | $0.0600 | 60% più economico |
Eseguirlo in autonomia o pagare l’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 calcolatore self-hosting vs API calcola il punto di pareggio in base al tuo volume di token.
Domande frequenti
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.
I prezzi indicati sono le tariffe ufficiali pubblicate per l'API principale del modello e vengono aggiornati man mano che i fornitori li modificano. Sconti per volumi elevati, elaborazione batch e input memorizzati nella cache non sono inclusi. Confronta tutti i modelli fianco a fianco nel database dei modelli AI o il Classifica LLM.