Explain This – select text, get an explanation from a local LLM
Explain This is a browser extension that provides plain-language explanations of selected text using a local LLM running via WebGPU. The extension downloads a quantized Llama 3.2 1B model the first time it is used and operates entirely offline thereafter. It leverages Chrome’s offscreen documents to run the model within Manifest V3 constraints.
- ▪The extension works in Chrome or Edge versions that support WebGPU, typically Chrome 113 or newer.
- ▪On first use, it downloads an 880 MB Llama 3.2 1B model and caches it in the browser for subsequent instant explanations.
- ▪The architecture uses a background service worker, an offscreen document for model inference, and a content script to display results.
- ▪Installation requires cloning the GitHub repository, building the project, and loading the unpacked extension in developer mode.
- ▪The model can be swapped by editing a constant in the source code, allowing larger models at the cost of a longer initial download.
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,864 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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/Vishwamitra/explain-this |
| Publication time | Thu, 30 Jul 2026 08:34:46 +0000 |
| Retrieval time | 2026-07-30T08:57:01.751Z |
| Last seen | 2026-07-30T08:57:01.751Z |
| 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 | w59dU_h6dSYB · 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
Explain This Select any text on a page, right-click, hit "Explain This," get a plain-language explanation. Runs entirely in your browser tab using a local LLM over WebGPU. No server, no API key, nothing ever leaves your machine. Why I was messing around with Ollama and vLLM locally for privacy-sensitive stuff (translating docs, RAG over my own notes) and got curious about WebLLM, which runs models straight in the browser via WebGPU instead of needing a separate server process. It used to be pretty slow and limited. Turns out it's gotten a lot better lately, so I built this to actually test it on something real instead of just reading benchmarks. Requirements Chrome or Edge, recent desktop version (needs WebGPU, which is Chrome 113+ roughly).
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.