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wire 2026-07-27
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LLAMA.CPP SHIPS MINIMAX-M3 SPARSE ATTENTION, VLLM UNLOCKS HETEROGENEOUS PREFILL-DECODE

By RepoJournal · Filed · About Local LLMs · Composed from the cited sources · methodology

The inference stack gets a new model architecture and a fundamental shift in how prefill and decode can run on different hardware configurations.

Llama.cpp landed full MiniMax-M3 support [2] [4] with vision tower integration, adding sparse attention capability to handle 60-layer, 128-expert MoE models where "a lightweight per-GQA-group indexer scores the visible causal context, max-pools the scores into 128-token key blocks, and selects the top-16 blocks" [6]. The model joins an expanding list of specialized architectures getting native dispatch. On the vLLM side, MoRIIO heterogeneous prefill-decode routing [7] is now live, enabling prefill and decode phases to run different parallelism strategies (TP vs DP+DP) on the same cluster, yielding measurably higher throughput and lower TTFT at scale on MI300X. SGLang shipped LoRA support under breakable CUDA graphs [8], restoring prefill graph acceleration to LoRA workloads, and added EmbeddingGemma [9] with bidirectional attention and mean pooling. Meanwhile, llama.cpp fixed critical routing bugs for model names with slashes [5], resolved iOS conversation import by detecting format from file contents [3], and Ollama pushed an mlx update [1]. This period saw 60 commits and 60 PRs across 4 core repos, with 5 releases shipping.

Action items

References

  1. [1] v0.32.5 ↗ ollama/ollama
  2. [2] model: Add MiniMax-M3 (MSA: MiniMax Sparse Attention) support (#24908) ↗ ggml-org/llama.cpp
  3. [3] ui: detect the conversation import format from file contents (#26121) ↗ ggml-org/llama.cpp
  4. [4] mtmd: Add Vision Support for Minimax-M3 (#25113) ↗ ggml-org/llama.cpp
  5. [5] server + ui: fix stream routes for model names containing a slash (#26137) ↗ ggml-org/llama.cpp
  6. [6] Add MiniMax-M3 (MSA: MiniMax Sparse Attention) support ↗ ggml-org/llama.cpp
  7. [7] [Core][KV-transfer] MoRIIO: heterogeneous TP<->DP prefill/decode read routing ↗ vllm-project/vllm
  8. [8] [LoRA] Support LoRA under the breakable/full prefill CUDA graph ↗ sgl-project/sglang
  9. [9] model: support EmbeddingGemma ↗ sgl-project/sglang

Quick answers

What shipped in Local LLMs on July 27, 2026?
The inference stack gets a new model architecture and a fundamental shift in how prefill and decode can run on different hardware configurations. In total, 60 commits, 60 pull requests, and 5 releases landed.
Who contributed to Local LLMs on July 27, 2026?
14 developers shipped this update, including github-actions[bot], dhiltgen, timkhronos, Pascal, AndreasKaratzas, walterbm, edwinlim0919, and zxd1997066, and 6 more.
What were the notable Local LLMs updates?
v0.32.5, model: Add MiniMax-M3 (MSA: MiniMax Sparse Attention) support (#24908), and ui: detect the conversation import format from file contents (#26121).