Meta Llama 3.3 70B Instruct

Who should use this model?

• highest-quality Llama 70B local chat target
• multilingual drafting and analysis
• agentic or tool-use workflows on high-memory systems
• local alternative when 405B is impractical

Choose something else when

• you have less than about 48 GB available memory for the model
• you need fast consumer-GPU inference
• you require an Apache-2.0 license

What hardware makes sense?

The download is only part of the memory needed. Leave room for the app, the input it processes, and other open programs. For chat models, context includes the instructions, conversation, and answer. Longer context needs more memory.

CPU only

Memory or response time may limit use. Try a smaller model first.

8GB system memory

Use a smaller model for this memory limit.

16GB system memory

Use a smaller model for this memory limit.

32GB system memory

Use a smaller model for this memory limit.

8GB GPU memory

Use a smaller model for this memory limit.

12GB GPU memory

Use a smaller model for this memory limit.

24GB GPU memory

Some model work must use system memory, which can slow responses.

Apple unified memory

Requires 64GB or more unified memory

Model facts that change the decision

Parameters

70B

Input

Text

Published context limit

128,000 tokens

Model format

safetensors · GGUF · Ollama

Suggested compression

Q4_K_M

Typical Q4 file

42.52GB before runtime and context overhead

Languages

English · German · French · Italian · Portuguese · Hindi · Spanish · Thai

Conditions that change the answer

• Memory needs include the model file, the app, and conversation memory. Longer conversations and other open apps need more space.
• Full-GPU Q4_K_M inference generally exceeds 24 GB VRAM; 24 GB cards require CPU offload, smaller quantization, shorter context, or a different model.