# StrataFlux preprint reports improved low-bit inference using streamed precision

_Published Friday, November 6, 2026 at 6:01 PM EST · AI, Science · Latest · Tier 2 — Notable_

Researchers presenting StrataFlux report that selectively streaming additional numerical precision from host RAM and solid-state drives can improve compressed language models without surrendering their memory advantages. The preprint describes overlapping transfers with computation and reusing fetched precision across generation steps.

For Qwen3-8B with 2-bit weights and key-value cache, the framework raised AIME 2024/2025 accuracy from 11.0% to 47.1% at unchanged GPU memory use. For 2-bit Llama-3.1-8B-Instruct weights on RTX 5090, it reduced WikiText-2 perplexity from 9.46 to 8.40 while retaining 95.4% of the compressed baseline's throughput. The findings come from evaluations of selected models on dedicated GPUs and unified-memory platforms.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2611.08363)

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Canonical: https://techandbusiness.org/newswire/nNmR1lb_WM5wQqrmWIC1Bh
Published: 2026-11-06T23:01:40.702Z
Story chronology: 2026-11-06T05:00:00.000Z
Retrieved: 2026-11-07T01:08:09.768Z
Publisher: Tech & Business (techandbusiness.org)