whichllm

AI

local llm model selection

SHOW HN2026

Legend

whichllm

Find the best local LLM for your hardware, ranked by benchmarks

github.com

#local llm#llm benchmarks#gpu vram#model selection

283points
68comments
#160of 4,366 in 2026
Top 4%of 2026 by points

How HN took it

MixedNo clear lean

6 positive, 15 neutral or asking, 2 mixed, 16 critical, out of 39 comments about the project. Thread score -0.23.

Idea: 2 for, 4 againstExecution: 0 for, 3 againstPerformance: 0 for, 3 against

The thread, comment by comment

Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.

positive neutral or mixed critical about another commenter or something else the maker

What HN said

What people liked

  • Useful concept for picking local models by hardware

    From 3 comments
    • Only thing I would add is the ability to point to new/uncataloged benchmarks. If I have a favorite benchmark that best matches my use-case, the ability to point to it and have it…
      zambelli on HN
    • Cool idea – the local LLM space really needs a tool like this that actually understands hardware and real benchmarks instead of just “biggest model that fits.”
      vaporaviatorlab on HN
    • Cool idea, thanks for making this
      wald3n on HN

Objections

  • Thread suspects AI-generated project and promotion; maker's account looks inauthentic

    From 3 comments
    • 1. The results of this tool are not good. It’s recommending outdated models like Qwen2.5 series and missing good new models. 2. Nothing about this needs to run on your local…
      Aurornis on HN
    • There is apparently a marketing.md file that was deleted 25min ago with the strategy to post on HN.…
      hazelnut on HN
    • OP is a newish user, all of their responses here are copied straight from Claude, and this project has an LLM slop readme (count them: 48 em-dashes on the page!) and LLM code.…
      rafram on HN
  • Recommends outdated models such as Qwen2.5 and misses newer ones

    From 2 comments
    • 1. The results of this tool are not good. It’s recommending outdated models like Qwen2.5 series and missing good new models. 2. Nothing about this needs to run on your local…
      Aurornis on HN
    • Brew install is broken It seems pretty rubbish I have to say, its recommending me loads of qwen 2.5 which are really old and I'm easy running qwen3.5 and 3.6 models on this mac…
      Bigsy on HN
  • Estimates only, does not measure speed on the user's machine

    From 1 comment
    • Cool, but it looks like it doesn’t actually test anything on your machine? It does hardware detection and then some lookups. Maybe I missed it but I really want a tool like this…
      pbronez on HN
  • Brew install reported broken

    From 2 comments
    • Brew install is broken It seems pretty rubbish I have to say, its recommending me loads of qwen 2.5 which are really old and I'm easy running qwen3.5 and 3.6 models on this mac…
      Bigsy on HN
    • Tried it on a 4060, got Qwen3-14B Q3_K_M. Matches what I actually run. Brew install failed for me too though (macOS 14.5).
      Bekamakhara on HN
  • Unified memory and iGPU detection is wrong

    From 2 comments
    • This doesn't correclty detect the unified memory architecture for GPU 0: STRXLGEN — 8.0 GB (ROCm 6.19.8-200.fc43.x86_64) — BW: N/A CPU: AMD RYZEN AI MAX+ 395 w/ Radeon 8060S — 16…
      cyanydeez on HN
    • it'd be nice if it had igpu support, it cant even detect it. overall great tool though. happy this exists.
      justindotdev on HN

Requests

  • Support use-case based recommendations such as coding or video

    From 2 comments
    • Interesting concept! A suggestion: `whichllm <USE_CASE>` would be more beneficial, i.e. `which coding` or `which text-to-video`.
      armcat on HN
    • "Best LLM" doesn't really depend on hardware alone. It actually depends more on your needs - type of workload, context length needed etc.
      zkmon on HN
  • Support sliding-window attention in VRAM estimates

    From 2 comments
    • The plan command is clever. How do you handle the VRAM estimation for models with sliding window attention vs full context? Something like Mistral at 32k context uses way less KV…
      Jasssss on HN
    • Nice! Mistral 7B v0.1 is sliding_window: 4096 in the HuggingFace config.json (though v0.2 sets it to null). Gemma 2 alternates sliding window (4096) and full attention every…
      Jasssss on HN
  • Add more quantization formats such as IQ3_M

    From 1 comment
    • can you add in the other quants like IQ3_M? also my personal simple rule of thumb for local ai sizing is: max model size (GB) = ram (GB) / 1.65
      macwhisperer on HN
  • Allow custom benchmarks

    From 1 comment
    • Only thing I would add is the ability to point to new/uncataloged benchmarks. If I have a favorite benchmark that best matches my use-case, the ability to point to it and have it…
      zambelli on HN

Questions

  • Where do the benchmark metrics come from

    From 1 comment
    • Where are the metrics being sourced from exactly? Externally? or does this project have benchmarks running somewhere for the purposes of this project. Latter would likely be more…
      drzaiusx11 on HN
  • How is the model selected, is AI used

    From 1 comment

Alternatives named

  • llmfit

    From 2 comments
    • What’s new regarding llmfit? https://github.com/AlexsJones/llmfit
      llagerlof on HN
    • Other than it (whichllm) being written in Python, nothing else. I just use llmfit.
      rvz on HN
  • canirun.ai

    From 2 comments
    • This is very helpful too: https://www.canirun.ai/
      jordiburgos on HN
    • canirun.ai does similar, but doesn't require any installs. I've found it to be pretty accurate for my setup too.
      Jeremy1026 on HN
  • artificialanalysis.ai

    From 1 comment
    • Not perfect, but I find the artificialanalysis.ai "Intelligence vs. Output Tokens Used in Artificial Analysis Intelligence Index" chart[0] (scroll down to the titled chart) to be…
      karmakaze on HN
  • RapidMLX

    From 1 comment
    • Cool, but it looks like it doesn’t actually test anything on your machine? It does hardware detection and then some lookups. Maybe I missed it but I really want a tool like this…
      pbronez on HN

Category, keywords, summaries and labels on this page were made by AI (Thread Reader v2) and not checked by hand. Each point links to the comments it came from.

Add a badge to your READMEShown on HackerShow
[![Shown on HackerShow](https://hackershow.org/badge.svg)](https://hackershow.org/show/48146369)