OMP NInfer
Decision guide
Choosing a local backend for coding sessions
Every project below is excellent at a different job. Most operators should use one of them; this page exists to make that call fast and honest.
| Dimension | OMP NInfer | Ollama | LM Studio | llama.cpp | vLLM |
|---|---|---|---|---|---|
| Primary job | Durable OMP appliance | Easy model runner | GUI model runner | Portable engine | General serving |
| Model breadth | One model, hash-pinned | Broad | Broad | Broad | Broad |
| Explicit Responses continuation | Core product | Verify current support | Verify current support | Verify current support | Verify current support |
| Process-restart recovery | Transactional checkpoints, verified restore | Different contract | Different contract | Different contract | Different architecture |
| GUI | No | Limited | Strong | No | No |
| Multi-user throughput | Not the target | Limited | Not the target | Limited | Strong |
| Best fit | One private, long-lived OMP session | Easy breadth | Desktop convenience | Portability | Serving scale |
Last verified 2026-08-31 against each project's public documentation. Capabilities change quickly — reverify before deciding.
The one-sentence answer
For an Oh My Pi operator running Qwen3.8 27B on a qualified RTX 5090, 4090, or 3090 who values private, restart-resumable long sessions, OMP NInfer is the strongest fit. Choose Ollama or LM Studio for breadth and convenience, llama.cpp for portability, or vLLM for serving scale.
Full criteria: decision guide · prior art: related work