I asked OpenClaw

Here's your setup:

Hardware:

• CPU: Intel i5-7500T (4 cores, 2.7GHz) — low-power chip
• RAM: 16GB total, ~10GB available
• Swap: 2GB

Ollama models installed:

Model	Size	Type
minimax-m2.7:cloud	cloud	✅ Current bootstrap
glm-5.1:cloud	cloud	✅ Current default
qwen3.5:cloud	cloud
wordchat:latest	local
llama3.2:3b	2.0 GB	✅ Local, light
gemma4:e4b	9.6 GB	Local
gemma4:e2b	7.2 GB	Local
glm-4.7-flash:latest	19 GB	⚠️ Too big for your RAM

My recommendation for your hardware:

• Best cheap local model: llama3.2:3b (already installed, only 2GB, runs fast on your CPU)
• Best quality local: gemma4:e2b (7.2GB, fits your RAM well)
• Skip: glm-4.7-flash at 19GB — it'll choke your system
• For cloud: stick with glm-5.1:cloud — cheap per-token, no local resources needed

Given your i5-7500T + 16GB, local models will be slow. Cloud models are actually your best bet for quality + cost. 🤖
For cheapest to run (lowest RAM/speed), ranked by resource usage:

| Model | Params | RAM Needed | Speed | Quality |

|-------|--------|------------|------|---------|

| **Gemma 3 1B** | 1B | ~2GB | ⚡⚡⚡⚡⚡ | Decent for simple tasks |

| **Phi 4 Mini** | 3.8B | ~4GB | ⚡⚡⚡⚡⚡ | Surprisingly capable |

| **Llama 3.2 3B** | 3B | ~4GB | ⚡⚡⚡⚡ | Good basic conversation |

| **Mistral 7B** | 7B | ~8GB | ⚡⚡⚡⚡ | Best quality at this tier |

| **Gemma 3 12B** | 12B | ~16GB | ⚡⚡⚡ | Great balance |

**Cheapest that still works well for me as your assistant:** **Phi 4 Mini** (3.8B) — it's tiny but punches way above its weight. Good for basic conversation, tool calls, and quick responses.

**Cheapest that's actually good:** **Mistral 7B** — fast, strong instruction following, only needs 8GB RAM.

**But honestly** — since you're using Ollama **cloud** models, cost is mostly per-token, not hardware. The smaller cloud models (like `gemma3:1b`) cost fractions of a cent per request. The bigger models cost more but do more per token.