magnitude vs Ollama
Local inference desktop app + CLI: profiles your hardware, estimates tok/s per model before download, tunes the one you pick, and connects Pi, OpenCode, Hermes, Codex or Claude Code in a click. — versus — Run Llama, Mistral and other open models locally with a single command and a clean API.
Both run open models locally behind an API your agents call; Ollama runs whatever you pull, Magnitude profiles your hardware first, then recommends and tunes the model for it.
| magnitude | Ollama | |
|---|---|---|
| Stars | 5.4k | 182k |
| Forks | 383 | 18k |
| Language | Rust | Go |
| License | Apache-2.0 | MIT |
| Last activity | today | yesterday |
| Topics | local | local |
| Curated connections | 2 | 29 |
magnitude — the curator's take
The on-ramp for people who do not know which model their machine can actually run: Magnitude profiles your hardware, ranks catalog models and quants by speed, accuracy and memory before you download, then tunes context size and speculative decoding for the one you pick and wires it into your coding agent. Models load on demand and unload when idle. That is the real difference from Ollama or LM Studio, which run whatever you choose. If you already know your model and want a scriptable server with a huge ecosystem, Ollama is the safer default; for multi-GPU serving, use vLLM. Young (launched June 2026) and moving fast.
Ollama — the curator's take
Run Llama, Mistral and other open models locally with a single command and a clean API.