Self-Hosting Quiz
Break-even maths, GPU sizing from weights and KV cache, choosing between vLLM, SGLang and llama.cpp, and what to scale and alert on once open-weight models carry production traffic.
Self-Hosting Quiz
Test your knowledge of self-hosted LLM deployment — vLLM, PagedAttention, TGI, GGUF, tensor parallelism, hardware selection, and Azure ML endpoints.
Apply the decisions to the scenario
Each question tests one decision from Read, not a definition. The explanation names the decision it checks.
1. What must a self-hosting break-even include?
2. Which is a strong reason to self-host?
3. Capacity was planned at 500 requests a minute, yet queues formed. What was missed?
4. The self-hosted model needs a maintenance window. What keeps non-sensitive features running?
Continue reading
All LLM Model Landscape articles →GPT: OpenAI's Model Family in Practice
The GPT-6 tiers, what reasoning effort replaced, when to use the Responses API over Chat Completions, how the bill is calculated, and what is different on Azure.
Claude: Anthropic's Model Family in Practice
The four Claude tiers, adaptive thinking and effort, the tool-use rules that differ from other providers, prompt caching, and where you can run it.
Llama: Open-Weight Models for Production
The Llama lineup and licence, serving with Ollama and vLLM, GPU memory sizing, and an honest look at when a hosted API is still the better choice.
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