Fast NF4 Dequantization Kernels for Large Language Model Inference explores Accelerate LLM inference by up to 2.2x with a plug-and-play dequantization kernel that leverages shared memory, reducing costs on existing GPU infrastructure.. Commercial viability score: 7/10 in LLM Inference Optimization.
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This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/fast-nf4-dequantization-kernels-for-large-language-model-inference
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID fast-nf4-dequantization-kernels-for-large-language-model-inference | Route /paper/fast-nf4-dequantization-kernels-for-large-language-model-inference
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/fast-nf4-dequantization-kernels-for-large-language-model-inferenceMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.02556"
}
}source_context
{
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"query": "Fast NF4 Dequantization Kernels for Large Language Model Inference",
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"route": "/paper/fast-nf4-dequantization-kernels-for-large-language-model-inference",
"paper_ref": "fast-nf4-dequantization-kernels-for-large-language-model-inference",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 7.0
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