Can Desktop PC · GeForce RTX 4080 SUPER · 32 GB RAM run MiniCPM5 2B?
16 GB VRAM + 32 GB RAM · 736 GB/s memory bandwidth · MiniCPM5 2B has 2.5B parameters.
Short answer
Yes, excellent for chat and acceptable or better for every workload we test.
Best quantization for chat: Q8_0 (2.5 GB of weights) on Ollama. Generation: 160–210 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 | Q8_0 | 160–210 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q8_0 | 150–200 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 130–180 tok/s | ≈1 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 120–170 tok/s | ≈1 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 90–120 tok/s | ≈4 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
Other models for Desktop PC · GeForce RTX 4080 SUPER · 32 GB RAM
The best-rated models for chat on this machine.
- gpt-oss-20b≈170 tok/sExcellent
- Gemma 4 26B-A4B170–230 tok/sExcellent
- Qwen3.5 9B55–70 tok/sExcellent
- Qwen3.5 4B95–130 tok/sExcellent
- Gemma 4 12B45–60 tok/sExcellent
- GLM-4.6V-Flash (10B)50–70 tok/sExcellent
Cheapest machines for MiniCPM5 2B
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.