CAcapnjngl·Sep 29, 2026
I don't know about that specific use case, but llmfit is your friend here https://github.com/AlexsJones/llmfit
In GLM-5.3 and the spread of advanced cyber capabilitiesAlexsJones
llmfit
Rust2026–2026
AlexsJones / llmfit
llmfit
Hundreds of models & providers. One command to find what runs on your hardware.
15Distinct people
15Mentions
1Explicit recommenders
39KGitHub stars
What to know before exploring
What it is
Hundreds of models & providers. One command to find what runs on your hardware.
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
I recommend llmfit. It shows you exactly what models you can run and at what speeds https://github.com/AlexsJones/llmfit
efilife used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.
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Also in these discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month15 dated mentions
Observed mentions: 2026-02-17 09:35:11 UTC to 2026-09-29 20:27:09 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Feb 2026 | 2026-02-01 00:00:00 UTC | 2026-03-01 00:00:00 UTC | 2 | 2 | 0 |
| Mar 2026 | 2026-03-01 00:00:00 UTC | 2026-04-01 00:00:00 UTC | 4 | 1 | 3 |
| Apr 2026 | 2026-04-01 00:00:00 UTC | 2026-05-01 00:00:00 UTC | 3 | 0 | 3 |
| May 2026 | 2026-05-01 00:00:00 UTC | 2026-06-01 00:00:00 UTC | 3 | 0 | 3 |
| Jun 2026 | 2026-06-01 00:00:00 UTC | 2026-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2026 | 2026-07-01 00:00:00 UTC | 2026-08-01 00:00:00 UTC | 1 | 0 | 1 |
| Aug 2026 | 2026-08-01 00:00:00 UTC | 2026-09-01 00:00:00 UTC | 1 | 0 | 1 |
| Sep 2026 | 2026-09-01 00:00:00 UTC | 2026-10-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
15 sourcesReminds me of https://github.com/AlexsJones/llmfit
In Show HN: Shoehorn – Quantize any model down to run on your machineI recommend llmfit. It shows you exactly what models you can run and at what speeds
https://github.com/AlexsJones/llmfit
In I built a page that tells you what AI model your laptop can runI got really good results when I asked Pi (agent) to install
https://github.com/AlexsJones/llmfit
and tell me which ones are good for me. It would organize it per use and selection was solid.
In Show HN: Find the best local LLM for your hardware, ranked by benchmarksThis has a web version[0] which I wish they'd host on a free site.
[0] https://github.com/AlexsJones/llmfit/tree/main/llmfit-web
Edit: I tried to deploy a snapshot of the llmfit-web files on Netlify but it seems to need/want to talk to a backend[1]
[1] https://llmfit.netlify.app/
In Show HN: Find the best local LLM for your hardware, ranked by benchmarksWhat’s new regarding llmfit?
https://github.com/AlexsJones/llmfit
In Show HN: Find the best local LLM for your hardware, ranked by benchmarkshttps://github.com/AlexsJones/llmfit gives a good approximation of that.
In Qwen3.6-27B: Flagship-Level Coding in a 27B Dense ModelYou are experiencing the fact that you might not have enough VRAM to load the entire model at a time. You might want to try https://github.com/AlexsJones/llmfit
In Qwen3.6-Max-Preview: Smarter, Sharper, Still EvolvingYou can try https://github.com/AlexsJones/llmfit
In Qwen3.6-Max-Preview: Smarter, Sharper, Still EvolvingWhy were you surprised?
You can check out here how it does that: https://github.com/AlexsJones/llmfit/blob/main/llmfit-core/s...
To detect NVIDIA GPUs, for example: https://github.com/AlexsJones/llmfit/blob/main/llmfit-core/s...
In this case it just runs the command "nvidia-smi".
Note: llmfit is not web-based.
In Can I run AI locally?Is this just llmfit but a web version of it?
https://github.com/AlexsJones/llmfit
In Can I run AI locally?>I only wish this was a website. I don’t like the idea of running an executable for something that can perfectly be done as a website.
The tool depends on hardware detection. From https://github.com/AlexsJones/llmfit?tab=readme-ov-file#how-... :
How it works
Hardware detection -- Reads total/available RAM via sysinfo, counts CPU cores, and probes for GPUs:
NVIDIA -- Multi-GPU support via nvidia-smi. Aggregates VRAM across all detected GPUs. Falls back to VRAM estimation from GPU model name if reporting fails.
AMD -- Detected via rocm-smi.
Intel Arc -- Discrete VRAM via sysfs, integrated via lspci.
Apple Silicon -- Unified memory via system_profiler. VRAM = system RAM.
Ascend -- Detected via npu-smi.
Backend detection -- Automatically identifies the acceleration backend (CUDA, Metal, ROCm, SYCL, CPU ARM, CPU x86, Asce
Read the rest
nd) for speed estimation.
Therefore, a website running Javascript is restricted by the browser sandbox so can't see the same low-level details such as total system RAM, exact count of GPUs, etc,
To implement your idea so it's only a website and also workaround the Javascript limitations, a different kind of workflow would be needed. E.g. run macOS system report to generate a .spx file, or run Linux inxi to generate a hardware devices report... and then upload those to the website for analysis to derive a "LLM best fit". But those os report files may still be missing some details that the github tool gathers.
Another way is to have the website with a bunch of hardware options where the user has to manually select the combination. Less convenient but then again, it has the advantage of doing "what-if" scenarios for hardware the user doesn't actually have and is thinking of buying.
(To be clear, I'm not endorsing this particular github tool. Just pointing out that a LLMfit website has technical limitations.)
Right-sizes LLM models to your system's RAM, CPU, and GPU
301 points · Open discussionA tool to tell you what LLMs can run on your machine
2 points · Open discussionShow HN: Llmfit;94 models, 30 providers.1 tool to see what runs on your hardware
I built this to justify to myself buying a more powerful laptop. Now you can too..
1 points · Open discussion