Deployment Advisor

Recommend the best deployment solution based on your scenario, hardware, and team conditions

中文 | English

1Use Case & Goals

2Hardware & Scale

3Experience & Preference

4Recommendation

Step 1: Use Case & Goals

Primary Use *

👤 Personal Experiment / Local Chat Try out LLMs yourself, or run a chatbot locally 💻 Development / Prototyping Building AI apps and need API endpoints for testing 👥 Team Internal API Provide a unified model service for your team or department 🚀 Production-Grade High-Concurrency Service User-facing product deployment requiring stability and throughput

Top Priority *

Simple & Hassle-Free Low Long-Term Cost Throughput & Latency Data Privacy

Step 2: Hardware & Scale

Hardware *

💻 No GPU 🍎 Mac / Integrated Graphics 🎮 Single Consumer GPU (8-24GB) 🖥️ Multiple GPUs / Server

Expected Concurrency

Personal Use

1 10 100 1K 10K

Specific Model Needs (Multi-select, optional)

Strong Chinese Coding Ability Multimodal Tool Calling (Function Calling) No Special Requirements

Step 3: Experience & Preference

Deployment Experience *

Just Getting Started Know Docker & Basic Linux Familiar with GPU Serving & Monitoring

Deployment Preference *

Prefer Local / On-Premise Cloud Is Also Acceptable Prefer Cloud (No Ops)

Budget Sensitivity *

Tight Budget, Minimize Cost Moderate, Best Value First Generous Budget, Prioritize Experience

Step 4: Recommendation