Can Laptop · GeForce RTX 4090 Laptop · 32 GB RAM run MiniCPM5 2B?
16 GB VRAM + 32 GB RAM · 576 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: 100–170 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 | 100–170 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q8_0 | 95–160 tok/s | under 1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 85–140 tok/s | ≈2 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 80–130 tok/s | ≈2 s | 32K | Details |
| Long documents (64K)with Open WebUI | Comfortable | Q8_0 | 60–95 tok/s | ≈6 s | 64K | Details |
Speeds are bandwidth-based estimates; no direct benchmark exists for this pair. “First reply” is the time to read the workload’s opening prompt. How we calculate
Other models for Laptop · GeForce RTX 4090 Laptop · 32 GB RAM
The best-rated models for chat on this machine.
- gpt-oss-20b100–170 tok/sExcellent
- Gemma 4 26B-A4B110–190 tok/sExcellent
- Qwen3.5 9B35–55 tok/sExcellent
- Qwen3.5 4B65–100 tok/sExcellent
- Gemma 4 12B30–45 tok/sExcellent
- GLM-4.6V-Flash (10B)35–55 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.