Llama 3.1 8B — Specifiche
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Sviluppatore | Meta |
|---|---|
| Tipo | LLM (densa) |
| Modalità | Testo → Testo |
| Parametri | 8B |
| Finestra contestuale | 128K |
| Licenza | Llama 3.1 Community (open) |
| Pesi aperti | Sì |
| Pubblicato | 2024 |
| Prezzo dell’input | $0.02 /1M |
| Prezzo dell’output | $0.03 /1M |
| Provider API | Together, DeepInfra, OpenRouter, Ollama |
Esegui localmente
| VRAM (4-bit) | ~5 GB |
|---|---|
| GPU minima | Qualsiasi GPU da 8 GB |
What is Llama 3.1 8B?
Llama 3.1 8B is the workhorse small Llama — 8B parameters, a 128K context, and about 5 GB
of VRAM at 4-bit, which runs on essentially any modern 8 GB GPU. It is one of the most widely
deployed open models in production and remains an excellent cheap baseline.
Its enduring value is less about capability than about ubiquity. Because it has been in
production for so long across so many stacks, it is the model with the deepest tooling
support, the most fine-tunes, the most quantised variants and the most known-good deployment
recipes — Ollama, vLLM, llama.cpp, Together, DeepInfra and OpenRouter all serve it without
surprises. That makes it the right choice for the first version of almost any local
deployment: get the pipeline working against a model that definitely runs, measure real
quality on your own data, then decide whether you need something larger. At $0.02 in / $0.03
out per million tokens the hosted price is close to a rounding error, so it also works well
as the cheap tier of a routing setup that escalates only when needed.
Llama 3.1 8B pricing: API cost per 1M tokens
| Input (per ogni milione di token) | $0.0200 |
|---|---|
| Output (per ogni milione di token) | $0.0300 |
| Rapporto output/input | 1.5× |
| Combinato (4:1 in:out) | $0.0220 per 1 milione di token |
What Llama 3.1 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 | $0.03 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $0.55 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $5.50 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Eseguirlo in autonomia o pagare l’API?
Llama 3.1 8B is open-weight, so you can run it yourself. It needs ~5 GB of VRAM at 4-bit (Any 8GB GPU). 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 Llama 3.1 8B cost per 1M tokens?
Llama 3.1 8B costs $0.0200 per 1M input tokens and $0.0300 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.0220 per 1M tokens.
How much does Llama 3.1 8B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $0.55 on Llama 3.1 8B. A side project (1M in / 0.25M out) costs roughly $0.03.
Can I run Llama 3.1 8B locally?
Yes. Llama 3.1 8B is open-weight and needs about ~5 GB of VRAM at 4-bit quantisation (Any 8GB GPU).
Why does Llama 3.1 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. Llama 3.1 8B charges 1.5× 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 di modelli IA o il Classifica LLM.