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SageAttention-RDNA4

Quantized attention for AMD RX 9070 / 9070 XT (RDNA4, gfx1201) on Windows: SageAttention with a hand-written fp8 HIP kernel, 1.06-2x faster than the gfx12 port in PR #368.

This is 1 of 151 launches in open-weight model deployment and inference — see how it stacks up on momentum and crowding →

66 other launches read as similar to this one →

Details

External ID
1400749273
Source
GITHUB
Company
—
Product
SageAttention-RDNA4
Website domain
github.com
Launched
Oct. 1, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.042292490118577074
Tags
amd, attention, comfyui, fp8, hip, rdna4, rocm, sageattention
Fetched at
Oct. 5, 2026, 5:03 p.m.
Updated at
Oct. 5, 2026, 5:03 p.m.

Enrichment

Niche
open-weight model deployment and inference
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
quantized attention kernel for amd rdna4 gpus
Manually corrected
False

Could you build this?

No Writing hand-optimized fp8 HIP GPU kernels for AMD RDNA4 hardware architectures requires deep low-level GPU microarchitecture and compiler knowledge.

What it would actually take: Requires deep understanding of AMD CDNA/RDNA assembly and HIP/ROCm, tuning shared memory (LDS), warp shuffles, tensor/matrix core instructions for fp8 quantization, and hardware register pressure profiling to maximize compute throughput on gfx1201.

Competitors

Other products that read as similar to this one — 66 launches clear the similarity bar, closest 8 shown.

Attention rank: #65 of 67 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 294 days after the earliest competitor.

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