Show HN: InstinctFlash – Run 5B world-action models in real time on Jetson Thor
A high-performance serving framework for robotics models. Deploy on your workstation with the same Runtime API used on Jetson Thor. Setup · Reproduce. [2026/09/16] RTX 4090 support.
- ▪A high-performance serving framework for robotics models.
- ▪Deploy on your workstation with the same Runtime API used on Jetson Thor.
- ▪Setup · Reproduce. [2026/09/16] RTX 4090 support.
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Story provenance
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Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/General-Instinct/InstinctFlash |
| Publication time | Tue, 22 Sep 2026 15:20:06 +0000 |
| Retrieval time | 2026-09-22T17:08:53.225Z |
| Last seen | 2026-09-22T17:08:53.225Z |
| 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 | jamhPZOa0eSk · 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
A high-performance serving framework for robotics models. What's new 🔥 [2026/09/17] RTX 5090 support. Deploy on your workstation with the same Runtime API used on Jetson Thor. Setup · Reproduce. [2026/09/16] RTX 4090 support. Desktop inference and WebSocket serving with dedicated installation profiles. Setup · Reproduce. [2026/09/15] Full-source release. Eight robotics model families, acceleration kernels, and Python / WebSocket serving through one Runtime. Get started. [2026/09/15] Jetson Thor benchmarks. Up to 33.78× speedup with LingBot-VA @2V/4A, using FP8 and fewer sampling steps. Results · Reproduce. Results Prediction p50 on Jetson Thor (ms), measured September 15, 2026. We’ve seen up to 33.78× speedup with no observed loss in task performance in our real-robot tests.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.