Can Desktop PC · GeForce RTX 4090 · 32 GB RAM run Llama 3.1 8B Instruct?
24 GB VRAM + 32 GB RAM · 1008 GB/s memory bandwidth · Llama 3.1 8B Instruct has 8B parameters.
Short answer
Yes, excellent for chat; borderline for coding in a repository.
Best quantization for chat: Q6_K (6.3 GB of weights) on Ollama. Generation: 85–120 tok/s, leaving about 15 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 | 85–120 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Acceptable | Q6_K | 80–110 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Borderline | Q8_0 | 55–75 tok/s | ≈2 s | 32K | Details |
| Agentic codingwith OpenCode | Borderline | Q8_0 | 55–70 tok/s | ≈3 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 40–55 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-3.1-8B-Instruct-GGUF:UD-Q8_K_XL
Downloads 10.58 GB (UD-Q8_K_XL). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for Desktop PC · GeForce RTX 4090 · 32 GB RAM
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B240–330 tok/sExcellent
- Gemma 4 26B-A4B160–220 tok/sExcellent
- LFM2.5 24B-A2B360–490 tok/sExcellent
- Qwen3.5 35B-A3B240–330 tok/sExcellent
- GLM-4.7-Flash (30B-A3B)240–330 tok/sExcellent
- gpt-oss-20b≈210 tok/sExcellent
Cheapest machines for Llama 3.1 8B Instruct
Hardware rated comfortable or better for chat, lowest price first.
- Mac mini M4 16 GB$599 · 15–20 tok/sComfortable
- Mac mini M6 16 GB$899 · 17–30 tok/sExcellent
- MacBook Air M4 16 GB$999 · 15–20 tok/sComfortable
- Mac mini M4 24 GB$999 · 11–14 tok/sComfortable
- Mac mini M2 16 GB$999 · 13–18 tok/sComfortable
- MacBook Air M5 16 GB$1,099 · 15–25 tok/sExcellent
Same chip, other memory: 64 GB
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.