#ROCm

How Far Has AMD ROCm Come in Catching Up to CUDA?

Based on EE Times' interview with AMD AI Software VP Anush Elangovan, we assess the ROCm vs CUDA ecosystem gap. Includes hands-on experience with ROCm breaking four times on Strix Halo, plus practical guidance on choosing between NVIDIA, AMD, and Apple Silicon.

LLM-jp-4-32B-A3B on ROCm + Strix Halo: 41% Faster Than Qwen3.5

Benchmarking NII's LLM-jp-4-32B-A3B-thinking on EVO-X2 (Ryzen AI Max+ 395) with ROCm. 62.9 t/s vs Qwen3.5-35B-A3B's 44.7 t/s. Covers thinking control issues, KV cache trade-offs, knowledge cutoff, Japanese quality comparisons, code generation tests, and training data composition.

Running Lemonade on Strix Halo (EVO-X2): Vulkan Shared Memory Leaks and ROCm Stability

Real-world testing of AMD Lemonade v10.0.1 on Ryzen AI Max+ 395. LLM, image generation, speech recognition, and TTS running simultaneously, NPU Hybrid execution, Vulkan vs ROCm benchmarks, and discovering shared memory leaks.

AMD's Lemonade Local AI Server Bundles GPU, NPU, and Multi-Modal Inference Under One Roof

Lemonade is AMD's open-source local AI server that manages multiple backends like llama.cpp and FastFlowLM across GPU/NPU/CPU, serving text, image, and audio generation through an OpenAI-compatible API.

Abliterated Models in Ollama Were a Complete Failure — and the Official Version Was Fine All Along

All variants of huihui-ai's Qwen 3.5 abliterated produced garbage tokens. GLM-4.7-Flash abliterated had a broken chat template. The official version with thinking disabled turned out to be the right answer.