Llama 3.2 1B Instruct
Llama · Llama 3.2 Community License
The smallest Llama model. Runs on integrated GPUs and even CPUs. Useful for basic classification, simple Q&A, and as a draft model for speculative decoding. Limited reasoning capability.
- Parameters
- 1.24B
- Architecture
- Dense
- Context
- 131,072 tokens
- Released
- 2024-09-25
- Engines
- llama.cpp, ollama
- Builder Tools
- Ollama, LM Studio
Parameters
1.24B
VRAM
1.1 GB
Context
128K
Formats
4
GPUs
43
Llama 3.2 1B Instruct (1.24B) requires 1.1 GB VRAM at recommended quality (Q6_K). At efficient quality (Q4_K_M), it fits in 819 MB VRAM, making it compatible with the NVIDIA RTX 4060 Laptop (40-60W). On NVIDIA Grace Blackwell Ultra GB300, expect approximately 800 tok/s at Q8_0. For the best experience, Starter AI Desktop ($582) is recommended.
Source: OwnRig methodology
1.1 GB
Q6_K
0.9 GB
128K tokens
Chat
VRAM Requirements
| Quality | Quantization | VRAM | File Size |
|---|---|---|---|
| full | Q8_0 | 1.5 GB | 1.2 GB |
| recommended | Q6_K | 1.1 GB | 0.9 GB |
| recommended | Q5_K_M | 1 GB | 0.8 GB |
| efficient | Q4_K_M | 819 MB | 0.7 GB |
Context Length Impact
KV cache VRAM at Q6_K quality. Longer context = more memory.
| Context | KV Cache | Total VRAM |
|---|---|---|
| 2K | 0 MB | 1.1 GB |
| 4K | 102 MB | 1.2 GB |
| 8K | 102 MB | 1.2 GB |
| 16K | 307 MB | 1.4 GB |
| 32K | 512 MB | 1.6 GB |
| 64K | 1 GB | 2.1 GB |
| 128K | 2 GB | 3.1 GB |
Compatible GPUs
43 devicesShowing 43 of 43 entries
Builder Context
Llama 3.2 1B Instruct is commonly used with Ollama, LM Studio. For an AI coding workflow, pair it with an embedding model like nomic-embed-text for local RAG.
Recommended Builds
Complete PC builds that can run Llama 3.2 1B Instruct.
Frequently Asked Questions
- How much VRAM does Llama 3.2 1B Instruct need?
- Llama 3.2 1B Instruct requires 1.1 GB VRAM at recommended quality (Q6_K). At lower quality settings, it can fit in as little as 819 MB.
- What is the best GPU for Llama 3.2 1B Instruct?
- The NVIDIA Grace Blackwell Ultra GB300 delivers the best performance for Llama 3.2 1B Instruct, achieving 800 tok/s at Q8_0 with an excellent rating.
- Can I run Llama 3.2 1B Instruct on an RTX 4060 Ti?
- Yes. On the NVIDIA GeForce RTX 4060 Ti 16GB, Llama 3.2 1B Instruct runs at 120 tok/s (Q8_0, excellent).
- What quantization should I use for Llama 3.2 1B Instruct?
- For the best quality, use Q6_K (1.1 GB VRAM). If your GPU has limited VRAM, Q4_K_M (819 MB) is the most efficient option with acceptable quality.
- Is Llama 3.2 1B Instruct good for coding?
- Yes. Llama 3.2 1B Instruct is used with Ollama, LM Studio for local AI coding. For the best coding experience, pair it with an embedding model for local RAG.
Data confidence: estimated. Source
VRAM requirements are calculated from model parameters and may vary by inference engine, context length, and batch size. Performance estimates are based on community benchmarks and should be verified for your specific configuration.Llama is a trademark of its respective owner. OwnRig is not affiliated with or endorsed by the model creator.