Llama 3.1 Family — lokalny model AI od Meta
Autor: Jakub Rusinowski · Ostatnia aktualizacja:
Lider otwartych wag dla sprzętu konsumenckiego. Llama 3.1 oferuje ogromne okno kontekstowe 128k i w wielu benchmarkach dorównuje GPT-4o.
Warianty
Najmniejszy wariant Llama 3.1 Family potrzebuje około 6 GB VRAM przy Q4_K_M — skwantyzowane wagi plus narzut frameworka, bez pamięci podręcznej KV.
| Model | VRAM przy Q4 | VRAM | Kontekst | Uruchom |
|---|---|---|---|---|
| Llama 3.1 8B Instruct → 8B | ~5.6 GB | 128,000 | ollama run llama3.1 |
Pamięć to skwantyzowane wagi plus narzut przy Q4_K_M, liczone tym samym silnikiem co sprawdzarka GPU i VRAM.
Jak uruchomić Llama 3.1 Family lokalnie
Zainstaluj Ollama, a potem pobierz tag.
ollama run llama3.1Wybierz rozmiar powyżej, aby zobaczyć jego VRAM, szacowaną szybkość i polecenie instalacji.
Download Llama 3.1 Family — GGUF Quantizations
Pick a quantization and open it in LM Studio, Ollama, or Jan, or download the raw .gguf file directly. Quant list and sizes resolved from Hugging Face.
Llama 3.1 8B Instruct — GGUF quants · bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
| Quant | Size | Download (.gguf) |
|---|---|---|
| Q3_K_M | 3.41 GB (est.) | Meta-Llama-3.1-8B-Instruct-Q3_K_M.gguf |
| Q4_K_M | 4.83 GB (est.) | Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf |
| Q5_K_M | 5.67 GB (est.) | Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf |
| Q6_K | 6.56 GB (est.) | Meta-Llama-3.1-8B-Instruct-Q6_K.gguf |
| Q8_0 | 8.50 GB (est.) | Meta-Llama-3.1-8B-Instruct-Q8_0.gguf |
Download in LM Studio: lms get bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
Want this model on your phone? You can run it on your desktop with LM Studio and chat from your iPhone or iPad over an encrypted link — see Run LM Studio Models on Your Phone (LM Link).
Licencja
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Dotyczy: Llama 3.1 8B InstructPolecane GPU
Najtańsze GPU z naszego katalogu, które uruchomi Llama 3.1 Family lokalnie (min. 6 GB VRAM), to Intel Arc B570 (10 GB).
Czy uruchomię Llama 3.1 Family na moim GPU?
- Llama 3.1 Family na AMD Radeon RX 9060 XT 8GB
- Llama 3.1 Family na Intel Arc B570
- Llama 3.1 Family na Intel Arc B580
- Llama 3.1 Family na NVIDIA GeForce RTX 3060 (12GB)
- Llama 3.1 Family na NVIDIA GeForce RTX 3070
- Llama 3.1 Family na NVIDIA GeForce RTX 3070 Ti
- Llama 3.1 Family na NVIDIA GeForce RTX 3080 (10GB)
- Llama 3.1 Family na NVIDIA GeForce RTX 4060
- Llama 3.1 Family na NVIDIA GeForce RTX 4070
- Llama 3.1 Family na NVIDIA GeForce RTX 4070 Super
- Llama 3.1 Family na NVIDIA GeForce RTX 4070 Ti
- Llama 3.1 Family na NVIDIA GeForce RTX 5060
- Llama 3.1 Family na NVIDIA GeForce RTX 5060 Ti 8GB
- Llama 3.1 Family na NVIDIA GeForce RTX 5070
Llama 3.1 Family — najczęściej zadawane pytania
How much VRAM does Llama 3.1 Family need?
Llama 3.1 Family needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Llama 3.1 8B Instruct (6 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Llama 3.1 Family on an RTX 4090 (24 GB)?
Yes — Llama 3.1 Family runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for Llama 3.1 Family?
Q4_K_M is the best balance of quality and VRAM for Llama 3.1 Family in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Llama 3.1 Family with Ollama?
Install Ollama, then run: ollama run llama3.1. This downloads Llama 3.1 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.