Can Desktop PC · RTX PRO 6000 Blackwell · 128 GB RAM run MiniCPM5 2B?
96 GB VRAM + 128 GB RAM · 1792 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: 320–440 tok/s, leaving about 91 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 | 320–440 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q8_0 | 310–410 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 270–360 tok/s | under 1 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 250–340 tok/s | under 1 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 180–250 tok/s | ≈3 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 · RTX PRO 6000 Blackwell · 128 GB RAM
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B260–360 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct260–360 tok/sExcellent
- gpt-oss-120b≈180 tok/sExcellent
- Gemma 4 26B-A4B210–280 tok/sExcellent
- Qwen3.5 35B-A3B260–360 tok/sExcellent
- LFM2.5 24B-A2B530–720 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.