local-inference apple-silicon open-source llm-tooling on-device-ai

Nativ runs open models locally on Apple Silicon

MIT-licensed desktop app executes open LLMs directly on Mac hardware via MLX-VLM, eliminating cloud dependencies and API keys.

Summary

Developers get real-time telemetry (tokens/sec, memory, thermal state) for local inference tuning, plus endpoint integration for coding agents without vendor lock-in. Eliminates cold-start latency and keeps prompts off external servers.

Why it matters

Implementation verdict

Replaces cloud-dependent LLM clients (Claude, ChatGPT web) for M-series Macs. Requires macOS + M1+ hardware; supports image/video/audio modalities via MLX-VLM backend. Ready now—open-source, no onboarding friction. Trade-off: model size limited by device RAM.

Sources

1.Run open models locally on your Mac
2.Built on MLX-VLM and tuned for M-series unified memory and Metal — no wrappers, no translation layers
3.Live tokens/sec, memory pressure, thermal state, and time-to-first-token
4.100% open source
5.No accounts to create, no credits to buy, no data to sell

Dev Signal

Get briefs like this in your inbox — free, every weekday.

100+ sources compressed into one 4-minute read. Ranked, cited, implementation-ready.

Read the full issue →All briefs