Model name portability
Model name portability is the principle of writing app code that survives swapping the underlying LLM provider (Claude → GPT → Gemini → local) without rewriting prompts, tool definitions, or response parsing.
Tight provider coupling makes vendor-switch painful: different prompt formats, different tool-call schemas, different response shapes. Portability strategies: (1) use a multi-model SDK (Vercel AI SDK, LiteLLM, OpenRouter) that normalizes the request / response shape, (2) write prompts in vendor-neutral natural language (no `<system>` tags or vendor-specific markers), (3) use structured output via JSON schema (which all providers support similarly), (4) keep tool definitions in OpenAI / MCP format. Trade-offs: portability sometimes means missing vendor-specific features (Anthropic's prompt caching, OpenAI's function-calling strict mode, Google's grounding). Production reality: most teams stay multi-vendor for cost / fallback reasons, so portability work is rarely wasted.
When to use model name portability
- Any production app to avoid lock-in.
- Multi-vendor cost / fallback strategies.
Common mistakes
- Hardcoding one vendor's tool-call schema — painful to migrate later.
- Over-engineering portability for one-off prototypes — premature.
FAQ
What is model name portability?
Model name portability is the principle of writing app code that survives swapping the underlying LLM provider (Claude → GPT → Gemini → local) without rewriting prompts, tool definitions, or response parsing.
When should I use model name portability?
Any production app to avoid lock-in. Multi-vendor cost / fallback strategies.
What are the most common mistakes with model name portability?
Hardcoding one vendor's tool-call schema — painful to migrate later. Over-engineering portability for one-off prototypes — premature.
Related terms
- LLM gateway — An LLM gateway is the proxy layer between your app and one-or-many LLM providers — handles routing, fallback, caching, cost tracking, rate limiting, and observability. OpenRouter, LiteLLM, Portkey, Helicone, Cloudflare AI Gateway are 2026 leaders.
- Model router — A model router picks which language model handles each request based on cost, latency, or task type — the standard production pattern in 2026.
- Bring-your-own-LLM (BYO-LLM) — Bring-your-own-LLM (BYO-LLM) is the developer pattern where a tool or product lets users configure their own model and API key — instead of locking them into the product's bundled LLM.
Last updated: 2026-06-01. Raw markdown: https://promtable.com/glossary/model-name-portability.md.