VQV Signal

PRODUCT UPDATE WATCH TECHNICAL

Benjamin Marie releases "statistically lossless" GGUF quantizations of Qwen3.8 27B

According to a post on X by @bnjmn_marie, Benjamin Marie has released GGUF files of Qwen3.8 27B made with the SLQ method from IST Austria's DASLab, built on top of Unsloth's UD GGUFs. The author says these files are better and smaller than the SLQ models he published last week. The "lossless" claim comes from the author, and the source only confirms that the model and code pages exist. The post also covers costs and ideas for improvements.

Source: Scobleizer News Pulse (X) · x.com Found via Robert Scoble’s Scobleizer News Pulse · a post on X, not independently verified Published 2026-10-27T04:35:00+00:00 Detected 2026-10-27T09:23:31+00:00
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According to a post on X by @bnjmn_marie, Benjamin Marie has released GGUF files of Qwen3.8 27B made with the SLQ method from IST Austria's DASLab, built on top of Unsloth's UD GGUFs. The author says these files are better and smaller than the SLQ models he published last week. The "lossless" claim comes from the author, and the source only confirms that the model and code pages exist. The post also covers costs and ideas for improvements.

AI-assisted summary based on the listed source.

Benjamin Marie released GGUF files of Qwen3.8 27B made with the SLQ method from IST Austria's DASLab, built on top of Unsloth's UD GGUFs, and says they are better and smaller than the SLQ models he published last week. The "lossless" claim is the author's; I only confirmed the model and code pages exist. His...

Developers who run open-weight models locally may care about this, since the author says the new files are smaller than his previous SLQ releases. The "lossless" label rests on the author's own statement, so independent testing will matter. Readers should look for the cost details and improvement ideas in his write-up and for any outside benchmarks.

Signal Strength 90% Technical label WATCH Public Interest 36 Category PRODUCT UPDATE Reader Depth TECHNICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 44 Novelty Interest Score 94 Consequence Score 18 Curiosity Score 0 Shareability Score 53

VQV surfaced this signal because it is recent, relevant to Open Source LLMs, connected to Scobleizer News Pulse (X).