What are the top questions for choosing an LLM for coding?

Focus on context window (100K+ for repos), HumanEval scores (80%+), and stability under long prompts.

How to pick LLM for production apps?

Prioritize TTFT <500ms, rate limits matching traffic, hardware fit, and 99.9% uptime SLAs.

Llama 3.1 70B edges on open benchmarks; Mistral Nemo for speed.

🤖 Large Language Models

Prioritize TTFT <500ms, rate limits matching traffic, hardware fit, and 99.9% uptime SLAs.

Llama 3.1 70B edges on open benchmarks; Mistral Nemo for speed.

Your LLM deployment crashes under load. Gibberish responses pile up. Here's the checklist devs swear by to avoid that nightmare.

theAIcatchup Apr 08, 2026 4 min read

Match model size and context to your prompts—overkill wastes cash, undersize fails. 𝕏
Test TTFT and stability in your stack; benchmarks lie without real workloads. 𝕏
Self-host open models to dodge API costs and lock-in, but verify ecosystem support. 𝕏

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#AI developer tools #AI development #AI evaluation #AI model evaluation #LLM evaluation #LLM selection #LLMs #choosing LLM #choosing LLMs #choosing an LLM #large language models #model evaluation #model selection

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Originally reported by InfoWorld