magnitude vs Strata
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 — Hybrid GPU/CPU MoE engine that runs Qwen3.8-Flash-Next and DeepSeek V4.1 on consumer cards: hot experts cached in VRAM, rest computed in RAM, MTP drafting, local OpenAI/Anthropic API.
Both are local-inference desktop apps plus CLI that pick a model for your hardware and connect it to Claude Code, Codex, OpenCode or Pi in one step; Magnitude spans many models, Strata goes deep on a few huge MoEs.
| magnitude | Strata | |
|---|---|---|
| Stars | 7.7k | 41k |
| Forks | 555 | 4.4k |
| Language | Rust | C++ |
| License | Apache-2.0 | MIT |
| Last activity | yesterday | yesterday |
| Topics | local | local, coding |
| Curated connections | 3 | 5 |
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.
Strata — the curator's take
Reach for it when you own a 12-24 GB GPU (NVIDIA, AMD, Apple Silicon) and want a frontier-class MoE behind Claude Code, Codex or OpenCode with no cloud — one installer, `strata connect` wires the tools. It is a purpose-built engine for a handful of model families, not a general runner: for arbitrary GGUFs or multi-user serving use Ollama/vLLM, and on low RAM or small disks the DeepSeek packs (200+ GB) will not fit.