Private
Nothing leaves the machine.
Every stage — parsing, embedding, training, inference — runs against local compute. ModelLM labels each operation local or cloud before it runs, and Private mode refuses to start any operation that would send your content off the machine.
- The material is confidential, regulated or under NDA
- You work somewhere that forbids third-party AI APIs
- You want a hard guarantee rather than a policy promise
- Workloads that genuinely need more compute than you own
Private company agent
An internal assistant that knows your documents, answers in your format, can act on internal systems, and never sends a byte outside the building.
Local coding AI
A completion and review model quantized to sit permanently in VRAM alongside your editor, with your source never leaving the machine.
Research assistant
Retrieval over a paper library with citations back to the source PDF. No training, no GPU required, minutes to build.
Qwen2.5 7B Instruct
7.6B · 32k · Apache 2.0
The default starting point for local work on 8–12 GB cards. Strong instruction following and reliable tool-call formatting for its size.
Qwen2.5 14B Instruct
14.8B · 32k · Apache 2.0
The sweet spot for 24 GB cards. Meaningfully stronger reasoning than 7B while still fine-tunable locally with QLoRA.
Qwen2.5 32B Instruct
32.8B · 32k · Apache 2.0
Approaches 70B quality at half the memory. Runs on a single 24 GB card at Q4_K_M with a modest context window.
Qwen2.5 72B Instruct
72.7B · 32k · Qwen License
Frontier-adjacent open weights. Needs a workstation, a multi-GPU rig or a large unified-memory Mac.
Qwen2.5 Coder 7B Instruct
7.6B · 32k · Apache 2.0
The practical local copilot. Supports fill-in-the-middle, so it works as an inline completion model rather than only a chat assistant.
Qwen2.5 Coder 32B Instruct
32.8B · 32k · Apache 2.0
The strongest open code model that still fits one 24 GB card. The reason a lot of people buy a 4090.