Can Desktop PC · Radeon RX 9070 XT · 32 GB RAM run Llama 3.2 3B Instruct?
16 GB VRAM + 32 GB RAM · 640 GB/s memory bandwidth · Llama 3.2 3B Instruct has 3.2B parameters.
Short answer
Yes, excellent for chat; not recommended for coding in a repository.
Best quantization for chat: Q6_K (2.5 GB of weights) on Lemonade. Generation: 150–200 tok/s, leaving about 11 GB free for your other apps.
How it rates for each workload
Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.
| Workload | Verdict | Quant | Generation | First reply | Context | |
|---|---|---|---|---|---|---|
| Chatwith Open WebUI | Excellent | Q6_K | 150–200 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Acceptable | Q8_0 | 110–150 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Technically Runs | Q6_K | 100–130 tok/s | ≈2 s | 32K | Details |
| Agentic codingwith OpenCode | Technically Runs | Q8_0 | 75–100 tok/s | ≈3 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 45–65 tok/s | ≈9 s | 64K | Details |
Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate
Get it running
Copy-paste commands for the Q8_0 build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.
ollama run hf.co/unsloth/Llama-3.2-3B-Instruct-GGUF:Q8_0
Downloads 3.42 GB (Q8_0). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for Desktop PC · Radeon RX 9070 XT · 32 GB RAM
The best-rated models for chat on this machine.
- gpt-oss-20b160–210 tok/sExcellent
- Gemma 4 26B-A4B170–240 tok/sExcellent
- MiniCPM5 2B160–220 tok/sExcellent
- Qwen3.5 9B55–75 tok/sExcellent
- Qwen3.5 4B100–130 tok/sExcellent
- Gemma 4 12B45–60 tok/sExcellent
Cheapest machines for Llama 3.2 3B Instruct
Hardware rated comfortable or better for chat, lowest price first.
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.