Model updates

Official news, first rumor reports and substantive progress. Each entry keeps the information published at that time.

• strix-llama rdna35-perf branch speeds Strix Halo prompt processing vs Vulkan and stock ROCm

  A LocalLLaMA author published the rdna35-perf branch on GitHub asf0/strix-llama.cpp (a Strix Halo–focused llama.cpp fork, ROCm/HIP only). On a Radeon 8060S / 128 GB Strix Halo box they report prompt processing 21–54% faster than Vulkan and up to about 2.7× faster than the stock ROCm kernel at 128k context with unchanged output quality, with the ROCm gap widening as context grows.

  OfficialOfficial updateOct 12Source: GitHub asf0/strix-llama.cppPart of llama.cpp
• llama.cpp merges probabilistic MTP drafting with rejection-sampling verify for ~14% faster prose decode

  llama.cpp pull request #27694 is merged: model-based drafters keep probabilistic samples and the target verifies with rejection sampling for simple draft and MTP, instead of discarding sampler output for the top candidate. A LocalLLaMA post reports about +14% decode on prose and recommends updating llama.cpp.

  OfficialOfficial updateOct 11Source: GitHub ggml-org/llama.cppPart of llama.cpp
• llama.cpp pull request adds a GPU cache for MoE experts kept in host memory, with up to 2.2x faster decode

  A llama.cpp pull request by am17an ports qvac-fabric's MoE expert cache, keeping an LRU cache of experts on the GPU and uploading only misses when experts live in host memory, enabled with --moe-cache-mib. Benchmarks on Qwen3.8-Flash-Next Q4_0 show 1.57-1.62x faster token generation on an RTX 4090 and up to 2.2x on an RTX 5090, per a post on r/LocalLLaMA. It currently supports single-GPU inference.

  UnconfirmedPublished newsOct 7Source: r/LocalLLaMAPart of llama.cpp
• User finds mainline llama.cpp beats ik_llama.cpp on a hybrid multi-GPU rig, per a Reddit post

  A post on r/LocalLLaMA says mainline llama.cpp consistently outperforms the ik_llama.cpp fork on the author's hybrid multi-GPU setup, despite recommendations to the contrary.

  UnconfirmedPublished newsOct 6Source: r/LocalLLaMAPart of llama.cpp
• llama.cpp v0.6.0 adds GLM-5.3-Flash 320B, Clef decision models and a /v1/systemone API

  llama.cpp released v0.6.0, headlined by support for the GLM-5.3-Flash (GLM5-Next) 320B text+vision hybrid model and the Clef decision model with both text and vision. The release ships a new /v1/systemone server API covering five decision models: laya, julia-1, lev, openjev (with vision) and kev. Qwen4Exp gets high-quality support with MTP speculative decoding, about a 1.5x decode speedup on DGX Spark. Other changes include a new llama_batch_ext API for mixed token/embedding inputs, an overhauled Web UI with a Hugging Face Hub data layer, Metal F16 KV flash attention and ggml v0.26.0.

  OfficialOfficial updateOct 5Source: ggml-orgPart of llama.cpp

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