{"slug": "turbo-fieldfare", "name": "turbo-fieldfare", "category": "ai", "category_name": "AI tools and apps", "description": "", "recommenders": 3, "commenters": 3, "warners": 0, "score": 2.908, "rising": 3.0, "first": "2026-08-14", "latest": "2026-10-27", "why": "All of these run perfectly fine on simple m4 silicone", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 3, "neutral": 0, "compare": 0, "warn": 0}, "spark": [0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1], "listed": true, "loved": [], "caveat": "", "short_quote": "All of these run perfectly fine on simple m4 silicone", "kind": "", "icon": false, "domain": null, "github_repo": "github.com/drumih/turbo-fieldfare", "official_url": "https://github.com/drumih/turbo-fieldfare", "pricing": "", "aliases": ["turbo-fieldfare", "TurboFieldfare"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 804250385, "item_id": 50265649, "url": "https://news.ycombinator.com/item?id=50265649", "by": "x3haloed", "date": "2026-10-27", "version": null, "stance": "recommend", "quote": "Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare", "excerpt": "Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read. Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.", "context": "", "use_case": "", "switched_from": "", "story": "Survival LLM: AI assistant and emergency library that runs on your own computer"}, {"id": 791053633, "item_id": 49440852, "url": "https://news.ycombinator.com/item?id=49440852", "by": "twobitshifter", "date": "2026-08-25", "version": null, "stance": "recommend", "quote": "Tools like turbo fieldfare are really reducing the memory requirements to run large models", "excerpt": "Why are we comparing to the maxed out model only? The M5 Ultra with 96 GB, 1 TB, and 64 GPU cores is $5499. Apple lets you lease that model for $110/month for 36 months. If you can settle for a M5 Max base model that would be a $49/month lease. Today, you should be able to run Qwen 3.8 - 27B amazingly well on either which is giving comparable performance to 5.6 Luna on SWE Bench. The local models are now getting bett", "context": "", "use_case": "", "switched_from": "", "story": "Apple introduces M6 and M5 Ultra"}, {"id": 788831344, "item_id": 49301959, "url": "https://news.ycombinator.com/item?id=49301959", "by": "literoldolphin", "date": "2026-08-14", "version": null, "stance": "recommend", "quote": "All of these run perfectly fine on simple m4 silicone", "excerpt": "Why is anyone even using video cards these days? You may as well be burning cash. This is the perfect candidate for just splattering it on your nvme and then reading it off there and into memory. All of these run perfectly fine on simple m4 silicone: https://github.com/drumih/turbo-fieldfare https://github.com/leonickson1/Swiftlet https://github.com/sqliteai/warp", "context": "", "use_case": "local LLM inference from NVMe", "switched_from": "", "story": "Qwen 3.8 27B is out: open weights, best local dense model yet"}, {"id": 786750400, "item_id": 49171900, "url": "https://news.ycombinator.com/item?id=49171900", "by": "gitpusher42", "date": "2026-08-04", "version": null, "stance": "recommend", "quote": "original TurboFieldfare supports Gemma", "excerpt": "Yeah, original TurboFieldfare supports Gemma https://github.com/drumih/turbo-fieldfare", "context": "", "use_case": "", "switched_from": "", "story": null}]}], "caveats": [], "who": [], "tags": [], "use_cases": ["local llm inference from nvme"], "compared": [], "makers": [{"id": 786124784, "item_id": 49132799, "url": "https://news.ycombinator.com/item?id=49132799", "by": "gitpusher42", "date": "2026-08-01", "version": null, "stance": "neutral", "quote": "The server is still experimental and I am fixing some problems currently.", "excerpt": "Thank you for testing and sharing results! I think I might understand your use case. You ssh the Mac and want something like `ollama run` with an interactive chat in terminal. Am I right? There is already experimental OpenAI-compatible server in this repo: ``` swift build -c release --product TurboFieldfareServer .build/release/TurboFieldfareServer \\ --model scratch/gemma4.gturbo ``` After that a small terminal clien", "context": "", "use_case": "", "switched_from": "", "story": "Show HN: Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac"}], "threads": [{"url": "https://news.ycombinator.com/item?id=50264853", "title": "Survival LLM: AI assistant and emergency library that runs on your own computer", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49433292", "title": "Apple introduces M6 and M5 Ultra", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49299605", "title": "Qwen 3.8 27B is out: open weights, best local dense model yet", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49158333", "title": "item 49158333", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49098510", "title": "Show HN: Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac", "mentions": 1}], "sentiment_by_month": {"2025-11": {}, "2025-12": {}, "2026-01": {}, "2026-02": {}, "2026-03": {}, "2026-04": {}, "2026-05": {}, "2026-06": {}, "2026-07": {}, "2026-08": {"recommend": 2}, "2026-09": {}, "2026-10": {"recommend": 1}}, "versions": [], "version_unnamed": 0, "family_ref": null, "runs_on": null, "lines": [], "quotes": [{"id": 804250385, "item_id": 50265649, "url": "https://news.ycombinator.com/item?id=50265649", "by": "x3haloed", "date": "2026-10-27", "version": null, "stance": "recommend", "quote": "Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare", "excerpt": "Decent LLMs can run on anything now: https://github.com/he-be/turbo-fieldfare Kiwix is great, but I'd also like a language model to be able to deeply interrogate all of that information much faster than I can read. Just arrange its harness so that its responses are grounded in the source material and require source citations for everything. Then read the citations to confirm it's not a hallucination.", "context": "", "use_case": "", "switched_from": "", "story": "Survival LLM: AI assistant and emergency library that runs on your own computer"}, {"id": 791053633, "item_id": 49440852, "url": "https://news.ycombinator.com/item?id=49440852", "by": "twobitshifter", "date": "2026-08-25", "version": null, "stance": "recommend", "quote": "Tools like turbo fieldfare are really reducing the memory requirements to run large models", "excerpt": "Why are we comparing to the maxed out model only? The M5 Ultra with 96 GB, 1 TB, and 64 GPU cores is $5499. Apple lets you lease that model for $110/month for 36 months. If you can settle for a M5 Max base model that would be a $49/month lease. Today, you should be able to run Qwen 3.8 - 27B amazingly well on either which is giving comparable performance to 5.6 Luna on SWE Bench. The local models are now getting bett", "context": "", "use_case": "", "switched_from": "", "story": "Apple introduces M6 and M5 Ultra"}, {"id": 788831344, "item_id": 49301959, "url": "https://news.ycombinator.com/item?id=49301959", "by": "literoldolphin", "date": "2026-08-14", "version": null, "stance": "recommend", "quote": "All of these run perfectly fine on simple m4 silicone", "excerpt": "Why is anyone even using video cards these days? You may as well be burning cash. This is the perfect candidate for just splattering it on your nvme and then reading it off there and into memory. All of these run perfectly fine on simple m4 silicone: https://github.com/drumih/turbo-fieldfare https://github.com/leonickson1/Swiftlet https://github.com/sqliteai/warp", "context": "", "use_case": "local LLM inference from NVMe", "switched_from": "", "story": "Qwen 3.8 27B is out: open weights, best local dense model yet"}, {"id": 786750400, "item_id": 49171900, "url": "https://news.ycombinator.com/item?id=49171900", "by": "gitpusher42", "date": "2026-08-04", "version": null, "stance": "recommend", "quote": "original TurboFieldfare supports Gemma", "excerpt": "Yeah, original TurboFieldfare supports Gemma https://github.com/drumih/turbo-fieldfare", "context": "", "use_case": "", "switched_from": "", "story": null}]}