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Organization · Verified on Hugging Face

Base Compute

basecompute

local AI, GPU kernels, performance optimisation, agentic research pipelines, automated research

Models in Library1
Datasets in Library0
Models on Hugging Face44
Followers19

Compare the published evidence

This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Text generation.

Reported licenses: apache-2.0. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Text generation

Qwen3.8-27B-BaseQuant-V1

Base Compute

Quantized builds of Qwen/Qwen3.8-27B in three sizes. On held-out text, each one is closer to the BF16 model than the unsloth dynamic quant of the same size. Each GGUF is no larger than its unsloth counterpart. The Small bundle needs baseRT 0.4.0 or later. KL divergence of each quant's next-token distribution from the BF16 model, ours beside unsloth's quant of the same size, measured in llama.cpp. Lower is closer to BF16. The percentage over each pair is our change against unsloth. On text that was not used to build these files, all three are 17–34% closer to BF16 than unsloth's quant of the same size. Each cell: unsloth KL / BaseQuant KL (change). Bold marks the lower KL. The prompts come…

Open weights apache-2.0