Local LLM Hardware Calc
Free tool · No sign-upWhich LLM can I run locally?Pick your hardware and what you want the model to do: chat, coding, reading PDFs and passports. Strict formatting and long arithmetic degrade first.Context length (working memory)2k tokens4k tokens8k tokens16k tokens32k tokens64k tokens128k tokens256k tokensHow much conversation or document the model holds at once. Every token costs KV-cache memory on top of the weights.New to this?
- ▪Free tool · No sign-upWhich LLM can I run locally?Pick your hardware and what you want the model to do: chat, coding, reading PDFs and passports.
- ▪Strict formatting and long arithmetic degrade first.Context length (working memory)2k tokens4k tokens8k tokens16k tokens32k tokens64k tokens128k tokens256k tokensHow much conversation or document the model holds at once.
- ▪Every token costs KV-cache memory on top of the weights.New to this?
2 outlets in our directory ran this story, first to last over 28 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ Can a Local LLM Run My AI Assistant? — Towards Data Science
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,645 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | Dubir Group |
| Canonical URL | https://dubir.net/tools/local-llm-hardware-calculator/ |
| Publication time | Wed, 12 Aug 2026 15:58:02 +0000 |
| Retrieval time | 2026-08-12T16:11:31.861Z |
| Last seen | 2026-08-12T16:11:31.861Z |
| 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 | lDWvAAYSUTb- · 2 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
Free tool · No sign-upWhich LLM can I run locally?Pick your hardware and what you want the model to do: chat, coding, reading PDFs and passports. The calculator lists the open models that fit, how much context they hold, roughly how fast they generate, and for everything that does not fit, why not.Your hardwareAppleNVIDIAAMDIntelOtherGeForceRTX 306012GB · 360 GB/sRTX 4060 Ti16GB · 288 GB/sRTX 5060 Ti16GB · 448 GB/sRTX 3090 (used)24GB · 936 GB/sRTX 409024GB · 1008 GB/sRTX 509032GB · 1792 GB/s2x RTX 309048GB · 936 GB/sWorkstation / data centreRTX 6000 Ada48GB · 960 GB/sRTX PRO 600096GB · 1792 GB/sA100 (used)80GB · 2039 GB/sH10080GB · 3350 GB/sGB10 desktopsDGX Spark128GB · 273 GB/sASUS GX10128GB · 273 GB/sA dedicated GPU keeps about 90% for the model; the rest goes to context and…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Dubir Group.
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