Use cases
Which AI model for your use case?
For every common engineering problem we picked 3-5 models — with one sentence on why each one. No top-10 lists, no invented numbers.
Code generation — which AI model writes the best code?
Coding workloads have specific demands: long contexts (whole repos), stable tool-use loops for agents, low hallucination on API signatures, and enough output tokens to return entire files. Reasoning modes help with multi-step refactors but are too slow for inline completion.
5 model picksOpen hubRAG (retrieval-augmented generation) — embeddings plus LLM for document search
RAG is the default architecture for Q&A over your own documents: an embedding model turns chunks and queries into vectors, a vector DB finds similar chunks, and a generative model answers with the retrieved passages as context. You need two models — one for embeddings, one for generation.
4 model picksOpen hubAgentic AI — autonomous agents with tool use and multi-step workflows
Agentic workloads mean: the model decides which tool to call when, reads results, plans the next step — across dozens of iterations without human approval. That puts three hard demands on the model: tool-call arguments must be syntactically and semantically correct (hallucinations break the chain), long contexts must survive drift, and reasoning modes help with plan synthesis.
4 model picksOpen hubBulk classification and routing — cheap AI for high volumes
If you're tagging, classifying, routing, or briefly summarizing millions of texts, a flagship model is pure money-burn. You need sub-500ms latency, costs in the cents-per-thousand range, and solid accuracy — not state-of-the-art reasoning. Mini and Haiku-tier models exist for exactly this.
4 model picksOpen hubImage generation — which AI model for which type of image?
Image generation splits today: dedicated diffusion models (Imagen, Flux) deliver top detail quality, while multimodal LLMs (Gemini, GPT-Image) are better at prompt following and text-in-image. For marketing visuals with logos and slogans, pick the latter; for realistic product renderings, pick the former.
2 model picksOpen hubMultilingual AI for the European market — GDPR-friendly
B2B workloads in Europe often hit the GDPR question: can data leave for the US? For many compliance setups the answer is no. Plus: quality across French, Italian, German, and Spanish varies between models far more than English does.
3 model picksOpen hub