Launch HN: Magnitude (YC S25) – Self-optimizing inference engine for agents
Magnitude Run open models as fast as your hardware allows Magnitude is an open source inference engine for agents that optimizes itself for your exact hardware. It compiles and tunes its kernels on your device, so open models run up to 2x faster than llama.cpp. One click connects the agent you already use (Pi, OpenCode, Hermes, Codex, and more).
- ▪Magnitude Run open models as fast as your hardware allows Magnitude is an open source inference engine for agents that optimizes itself for your exact hardware.
- ▪It compiles and tunes its kernels on your device, so open models run up to 2x faster than llama.cpp.
- ▪One click connects the agent you already use (Pi, OpenCode, Hermes, Codex, and more).
Hacker News (Front Page) files mainly under programming. We currently carry 2,319 of its stories. Top-voted stories on Hacker News.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/magnitudedev/magnitude |
| Publication time | Wed, 30 Sep 2026 17:37:40 +0000 |
| Retrieval time | 2026-09-30T17:47:01.800Z |
| Last seen | 2026-09-30T17:47:01.800Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | D_FntLgPcWco · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Magnitude Run open models as fast as your hardware allows Magnitude is an open source inference engine for agents that optimizes itself for your exact hardware. It compiles and tunes its kernels on your device, so open models run up to 2x faster than llama.cpp. One click connects the agent you already use (Pi, OpenCode, Hermes, Codex, and more). Works on Apple Silicon, NVIDIA, AMD, or nothing but a CPU. Download Magnitude for macOS, Windows, or Linux ⭐ Help us reach more developers and grow the Magnitude community. Star this repo! demo-9-29.mp4 Get started Download Magnitude, install it, and open the app. Choose a recommended model in Discover and download it. Connect your agent in Connections and start using it. The desktop app includes the magnitude CLI.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.