Can Desktop PC · GeForce RTX 5060 Ti 16GB · 32 GB RAM run MiniCPM5 2B?
16 GB VRAM + 32 GB RAM · 448 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: 110–140 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 | 110–140 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q8_0 | 100–140 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 90–120 tok/s | ≈2 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 85–110 tok/s | ≈3 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 60–80 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
Other models for Desktop PC · GeForce RTX 5060 Ti 16GB · 32 GB RAM
The best-rated models for chat on this machine.
- gpt-oss-20b≈100 tok/sExcellent
- Gemma 4 26B-A4B120–160 tok/sExcellent
- Qwen3.5 9B35–50 tok/sExcellent
- Qwen3.5 4B65–90 tok/sExcellent
- Gemma 4 12B30–40 tok/sExcellent
- GLM-4.6V-Flash (10B)35–45 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.