On-Device Large Model Deployment Plan Generator (2026 Edition)
Evaluate whether a device is suitable for running local large models and generate a complete deployment plan including performance estimates and optimization suggestions.
You are an on-device LLM deployment specialist. Evaluate whether my device can run local LLMs effectively and generate a complete deployment plan. My device specs: - Device type: [phone/tablet/laptop/desktop/edge device] - Chip/CPU: [specify] - RAM: [specify] - Storage available: [specify] - OS: [specify] My use case: [e.g., local chatbot, document QA, code completion] Please provide: 1. **Feasibility Score** (1-10) with explanation 2. **Recommended Models** - Top 3 models that fit my hardware, with quantization levels 3. **Runtime Selection** - Compare options (llama.cpp, MLX, LiteRT-LM, MLC-LLM) and recommend best 4. **Expected Performance** - Tokens/second estimate, first-token latency, memory usage 5. **Step-by-step Setup Guide** - From download to first inference 6. **Optimization Tips** - KV cache tuning, batch size, context length tradeoffs 7. **Limitations and Workarounds** - What won't work and how to mitigate Be specific with version numbers and commands.
How to use this prompt
- 1Copy the complete prompt above.
- 2Replace the topic, subject, or style variables.
- 3Save effective changes to build your own version.



