Best LLM for SQL generation in 2026: GPT-4o-mini wins clean
Four LLMs, six SQL tasks, one PostgreSQL schema. GPT-4o-mini led with 9 wins over Claude Sonnet 4.5, GPT-4o, and Gemini 2.5 Flash. Here's the full breakdown.
LLMTest Blog
Real-world guides on cutting LLM API costs, writing prompts that hold up, and comparing models — for solo developers, vibe coders, and indie hackers.
Four LLMs, six SQL tasks, one PostgreSQL schema. GPT-4o-mini led with 9 wins over Claude Sonnet 4.5, GPT-4o, and Gemini 2.5 Flash. Here's the full breakdown.
We ran 5 developer tasks through DeepSeek V4 Pro, GPT-5.5, Opus 4.7, and Llama 4. V4 Pro beats GPT-5.5 while costing 4.5x less, but latency averages 28 seconds.
Prompt caching cuts LLM costs 90% on Anthropic and 50% on OpenAI, but only when your workload fits. Here's the exact break-even math per provider.
The exact token-to-word and token-to-character conversion rates for English, code, and non-English LLM input, plus a practical counting recipe.
OpenAI's GPT-5.5 brings a 1M-token context and native computer use to the frontier, at double GPT-5.4's price. Here's what actually changed.
A 7-step framework for picking the right LLM for any job. Real constraints, real benchmarks, real routing. Stop guessing from leaderboards.
RAG has 3 moving parts: ingestion, retrieval, and generation. Here's what each does, when RAG beats fine-tuning, and when to skip it entirely.
Opus 4.7 scores higher on coding benchmarks and adds 3.75MP vision, but its new tokenizer inflates real cost by up to 35%. Here's what changed.
One model going down shouldn't take your AI feature with it. Here's how to build a fallback chain using LiteLLM, OpenRouter, and LLMTest.
Your OpenAI bill isn't just input + output tokens. Thinking tokens, JSON retries, and prompt bloat quietly triple costs. Here's how to spot each one in your own app.
The context window is your LLM's working memory per call. What 128k tokens actually fits, why usable size is smaller than advertised, and how to check yours.