13 related articles

Unsloth officially supports AMD GPUs across RDNA 3-4, Strix Halo, and MI300 series, delivering 2x training speedup and 70% VRAM savings on 500+ models with RL and vLLM weight sharing support.

A non-programmer tests AMD Ryzen AI Halo by deploying local AI models to tackle a real dev task. After testing Ollama and Qwen3, the verdict: AI amplifies developers, it doesn't replace them.

In-depth review of the AMD Ryzen AI Halo mini AI box: powered by the Ryzen AI Max Plus 395 (Strix Halo) chip with 128GB unified memory, priced at $4,000. Compared against NVIDIA's DGX Spark across token generation, prefill speed, and x86 advantages.

Open weight ≠ runnable locally. This article breaks down the hardware barriers, VRAM limits, electricity costs, and parallelism constraints of models like GLM 5.2 and DeepSeek — revealing where open-weight models truly add value: driving cloud competition, not home replication.

Unsloth v0.1.481-beta adds full DeepSeek-V4-Flash support, NVFP4/FP8/imatrix GGUF quantized export, 1.3x faster GRPO, 3-5x faster MoE training, and an OpenAI-compatible API service in Studio.

AMD officially unveils the Ryzen AI Halo local AI dev kit, priced around $4,000 with 128GB unified memory, capable of running 70B LLMs locally. An in-depth look at its specs, pricing, and market competition.

Unsloth v0.1.48-beta released, adding NVFP4/FP8 quantization export, OpenAI-compatible API hot-swapping, 3-5x faster MoE training, and 1.3x faster GRPO, covering the full LLM fine-tuning, quantization, and local deployment pipeline.

Unsloth v0.1.45-beta adds Gemma 4 MTP support, AMD ROCm & NVIDIA Blackwell fixes, a new Hub download manager, and a compact RAG system for local LLM fine-tuning.

Unsloth v0.1.464-beta adds DiffusionGemma, Gemma 4 MTP, and MiniMax-M3 support, delivering ~2x inference speed boost, new Hub, RAG Q&A, tensor parallelism, and full CUDA/ROCm/Windows coverage.

AMD Ryzen AI Halo dev kit at $4,000 features 128GB unified memory and XDNA 2 NPU for local LLM inference. Deep dive into architecture, performance trade-offs, vs. Mac Studio, and software ecosystem challenges.

AMD GPU black screens running local LLMs? This post-mortem covers Ollama's 3 fatal flaws and how switching to LM Studio boosted token speed from 5 to 36, with ROCm setup, Speculative Decoding, and GFX version tips.
TutorialsHow to build a fully automated invoice reimbursement system with local AI Agents, covering OCR, info extraction, and form generation with MinerU+Qwen3+Qianwen Po.