First production Vulkan LLM batch decode kernel on Radeon AI PRO R9700 — 1,724 tok/s, no CUDA, no ROCm

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Hi AMD community,

I want to share something we proved tonight that I think matters
for the R9700 ecosystem story.

We built Amalgis — a sovereign AI inference engine written entirely
in C and GLSL compute shaders. No PyTorch. No CUDA. No ROCm.
Pure Vulkan 1.1.

Tonight on a single Radeon AI PRO R9700 (RDNA4, 32 GB VRAM):

  • 1,724 tok/s throughput at batch=32 (Mistral 7B FP16)
  • 100% GPU utilization, flat — no CPU stalls, no idle
  • 82W power draw — 27% of 300W TDP
  • 46°C — no throttling
  • VRAM ceiling at 99% (31.7 GB / 31.9 GB confirmed)
  • All 32 concurrent sequences correct
  • git tag: vulkan-7b-batch32-proven

The core innovation: custom parallel batch attention kernel using
k_stack/v_stack flat KV buffers. 3 GPU dispatches total per layer
with Y-dimension = batch slot. Previously required 3 × batch_size
dispatches sequentially. 9 custom GLSL compute shaders written
from scratch in C.

Throughput scaling curve:
batch=1: 17 tok/s wall → 17 tok/s throughput
batch=4: 15 tok/s wall → 60 tok/s throughput
batch=8: 26 tok/s wall → 208 tok/s throughput
batch=16: 39 tok/s wall → 619 tok/s throughput
batch=32: 54 tok/s wall → 1,724 tok/s throughput ← VRAM ceiling

GPU telemetry at batch=32 (nvtop):
GPU utilization: 100% flat
VRAM: 31.7 GB / 31.9 GB (99%)
Power: 82W / 300W (27% TDP)
Temp: 46°C

This is not a ROCm benchmark. This is a custom Vulkan 1.1 compute
kernel that runs on any Vulkan-capable GPU — AMD, NVIDIA, Intel Arc,
Apple Silicon (MoltenVK). The R9700 is our production hardware.

The engine includes:

  • Custom FP16 QKV matmul (RDNA4 wave32 optimized)
  • RoPE with NTK-aware theta scaling
  • Parallel batch attention (k_stack/v_stack, Y=slot)
  • SwiGLU FFN
  • Hybrid RAG pipeline (cosine + IDF, inline, same GPU)
  • Per-tenant isolated document store
  • Air-gap capable, no cloud dependency

We are a DARPA SBIR applicant (FALCON DP2) building sovereign AI
infrastructure for enterprise and defense.

[attaching nvtop screenshot — 100% GPU, 99% VRAM, 82W, 46°C]

Happy to answer questions on kernel architecture, Vulkan dispatch
strategy, or GLSL shader design.

— Steven Hasson
Founder & CEO, Omniapan AI Inc.
DARPA FALCON DP2 applicant