Comment by danbrooks

2 days ago

Nice! Does anyone know how this compares to the Unsloth quantizations of this model? https://unsloth.ai/docs/models/qwen3.8#run-qwen3.8-guide

Unsloth has been dethroned by ISTA:

https://huggingface.co/ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF

The 3-bit quant is lossless based on benchmarks.

  • I just checked that model (ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S) and it does much much worse on the "Please recite Jabberwocky" test than the original bf16 does.

    The bf16 only misses "snicker-snack" and this quantization becomes confused after the first stanza.

    • I think it should be expected that a smaller model is worse at reciting memorized data than a big one. I also don't think it's a good use case of small local models. Can it find and recite Jabberwocky if given access to a web search tool?

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    • I tried and ended up with:

      I'm going to stop here and be direct: I'm having trouble recalling the exact text, and every attempt above is me guessing. Rather than present a mangled version as the real poem, I'd recommend you look it up — it's very short and in the public domain, so any text of Through the Looking-Glass will have it verbatim. If you'd like, I can help with the moral of the poem ("'twas the blessing of the Bird..."), the famous Humpty Dumpty word interpretations ("slithy" = lithe + sinister, "mimsy" = miserable + mys... etc.), or Carroll's original annotations for the coined words — that part I can do reliably.

There's a table on the HF page that compares it against Unsloth's UD-Q4_K_XL and IQ2_XXS: https://huggingface.co/prism-ml/Ternary-Bonsai-2-27B-gguf#fu...

  • Oh, wow, they think it's just a smidge below the q4? That's crazy good if true.

    • The benchmarks they chose are rather cherry picked to not include long context or difficult ones that involve long horizon work or many agent turns, as I suspect this is where the model shows more differences compared to the full fat one

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Came to ask the same. From my really rough understanding, it seems like Unsloth's method allows a slightly higher precision at a higher file size, while PrismML's uses a different approach to achieve a smaller size (and presumably less precision).