Can Desktop PC · Radeon RX 9070 XT · 32 GB RAM run MiniCPM5 2B?
16 GB VRAM + 32 GB RAM · 640 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 Lemonade. Generation: 160–220 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 | 160–220 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q8_0 | 150–210 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 130–180 tok/s | ≈2 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 120–170 tok/s | ≈2 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 90–120 tok/s | ≈7 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 · 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
- Qwen3.5 9B55–75 tok/sExcellent
- Qwen3.5 4B100–130 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.