Llama Models: The Most Popular Local AI
Meta's Llama is the most widely used open-weight model family in the world. The Llama 4 generation is multimodal MoE: Scout at 109B total / 17B active with 10M context, and Maverick at 400B total / 17B active, both of which want a 96GB+ Mac Studio rather than a laptop. The 3.x sizes remain the everyday local picks, from 1B and 3B on small machines up to 8B, 70B and 405B as memory allows. With the largest ecosystem of fine-tunes, tools, and community support, Llama is the safest default choice for local AI.
Meta12 local models
DEVELOPER
Meta
MODELS
12
SIZE RANGE
1B–405B
RAM RANGE
2–320 GB
Key Features
Most popular open-weight model family
Strong general reasoning and instruction following
Llama 4 Scout: 109B MoE with 10M context
Llama 3.x sizes from 1B to 405B for any machine
All Llama Models
| Model | Size | Quant | VRAM | Min RAM | Best For | Quality | Ollama |
|---|---|---|---|---|---|---|---|
| Llama 3.2 1B Instruct | 1B | Q4_K_M | 1 GB | 2 GB | Chat | 48 | |
| Llama 3.2 3B Instruct | 3B | Q4_K_M | 2.5 GB | 4 GB | Chat | 66 | |
| Llama 3.1 8B Instruct | 8B | Q4_K_M | 6.5 GB | 12 GB | Chat, Coding | 76 | |
| Llama 3.1 8B Instruct (Q8) | 8B | Q8_0 | 8 GB | 16 GB | Chat, Coding | 78 | |
| Llama 3.1 8B Instruct (Q5) | 8B | Q5_K_M | 8 GB | 12 GB | Chat, Coding | 78 | |
| Llama 3.1 70B Instruct | 70B | Q4_K_M | 42 GB | 64 GB | Quality, Coding | 84 | |
| Llama 3.3 70B Instruct | 70B | Q4_K_M | 42 GB | 64 GB | Quality, Coding | 86 | |
| Llama 3.3 70B Instruct (Q8) | 70B | Q8_0 | 75 GB | 96 GB | Quality, Coding | 88 | |
| Llama 3.3 70B Instruct (Q6) | 70B | Q6_K | 57.9 GB | 96 GB | Quality, Coding | 87 | |
| Llama 4 Scout | 109B | Q4_K_M | 67 GB | 96 GB | Long context, Quality, Multimodal | 88 | |
| Llama 4 Maverick | 400B | Q4_K_M | 245 GB | 320 GB | Frontier quality, Long context | 90 | |
| Llama 3.1 405B Instruct | 405B | Q4_K_M | 243 GB | 320 GB | Quality, Reasoning, Coding | 87 |
Device Compatibility
Which Llama models can run on each device class, based on minimum RAM requirements.
| Model | iPhone | Air | Pro | Studio | Mini |
|---|---|---|---|---|---|
| Llama 3.2 1B Instruct (1B) | Excellent | Excellent | Excellent | Excellent | Excellent |
| Llama 3.2 3B Instruct (3B) | Excellent | Excellent | Excellent | Excellent | Excellent |
| Llama 3.1 8B Instruct (8B) | Possible | Possible | Possible | Excellent | Possible |
| Llama 3.1 8B Instruct (Q8) (8B) | No | Possible | Possible | Excellent | Possible |
| Llama 3.1 8B Instruct (Q5) (8B) | Possible | Possible | Possible | Excellent | Possible |
| Llama 3.1 70B Instruct (70B) | No | No | Possible | Possible | Possible |
| Llama 3.3 70B Instruct (70B) | No | No | Possible | Possible | Possible |
| Llama 3.3 70B Instruct (Q8) (70B) | No | No | Possible | Possible | No |
| Llama 3.3 70B Instruct (Q6) (70B) | No | No | Possible | Possible | No |
| Llama 4 Scout (109B) | No | No | Possible | Possible | No |
| Llama 4 Maverick (400B) | No | No | No | Possible | No |
| Llama 3.1 405B Instruct (405B) | No | No | No | Possible | No |
RAM Requirements
1 GB · min 2 GB
2.5 GB · min 4 GB
6.5 GB · min 12 GB
8 GB · min 16 GB
8 GB · min 12 GB
42 GB · min 64 GB
42 GB · min 64 GB
75 GB · min 96 GB
57.9 GB · min 96 GB
67 GB · min 96 GB
245 GB · min 320 GB
243 GB · min 320 GB
Frequently Asked Questions
What is the best Llama model for a MacBook?
Llama 3.2 3B for MacBook Air (8GB RAM) or Llama 3.1 8B for MacBook Pro (16GB+ RAM). The 8B model is the community favorite for general-purpose local AI.
Can Llama 70B run on a Mac?
Yes, but you need at least 48GB RAM (Mac Studio or maxed-out MacBook Pro). The Q4 quantized version uses about 42GB. Expect around 8-12 tokens per second on M4 Max. The newer Llama 4 Scout is far heavier: 67GB loaded, so a 96GB or 128GB Mac Studio.
What is the difference between Llama 3.1 and 3.2?
Llama 3.2 added small sizes (1B, 3B) optimized for edge devices and mobile. Llama 3.1 covers 8B, 70B, and 405B. For most users, pick 3.2 3B for small devices or 3.1 8B for laptops.
How does Llama compare to Qwen?
Llama has stronger general reasoning and a larger community. Qwen has more size options and better multilingual support. At 7-8B, they are close in quality. Pick based on your use case.
