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wire 2026-09-19
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Ollama exposes thinking levels, llama.cpp widens Hexagon and architecture coverage

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

Ollama made per-model reasoning controls discoverable through its API, llama.cpp pushed more architectures and Hexagon kernels through CI, and vLLM added back-pressure detection to its KV cache tiering manager.

api: expose model thinking levels and defaults ollama/ollama

by ParthSareen

The /api/show endpoint and `ollama show` now report each model's supported thinking values and their defaults through an optional `thinking` object holding `values` and `default`, so clients like Codex CLI can populate reasoning-level controls from the model itself rather than hardcoding them. Older local templates pick up the metadata without a re-pull, and generic renderers preserve known lev...

[KV Offloading] Back-pressure detection and remediation vllm-project/vllm

by bnellnm

The KV cache tiering offloading manager now watches store completion latency via an exponential moving average and stops cascading new stores to a saturated tier (disk, shared storage, or P2P) until it recovers, rather than letting unbounded job pileup degrade serving latency. Operators running multi-tier offload get a serving path that degrades instead of snowballing.

hexagon: support for HMX flash-attention head_dim not multiple of 64 ggml-org/llama.cpp

by tboinovski1

The Hexagon HMX flash-attention kernel now handles head_dim values that are not multiples of 64, such as SigLIP's head_dim=72, by internally padding DK/DV to the next multiple of 64 with zero-filled tail lanes. Those shapes previously fell back to the slower HVX/CPU path, so multimodal models on Hexagon hardware now stay on the accelerated kernel.

Model-Saver: Write the SWA pattern, 15 more architectures roundtrip ggml-org/llama.cpp

by ServeurpersoCom

The model saver gained the SWA pattern, which pulls 15 additional architectures into the dummy-model, roundtrip, save/load-state, and fusion tests. A full local run of test-llama-archs on CPU and CUDA reports 254 roundtrips green, and the diff is mostly the same one-line substitution in a loader across 18 of its 21 touched files.

perf(sampling): avoid GPU syncs when applying custom logit processors sgl-project/sglang

by draftbk

Custom logit processors now cache CPU request rows and GPU indices instead of syncing per application; in one measurement on Qwen3.5-0.8B at batch size 1 on a B200 in BF16, time to first token moved from 18.60 ms to 17.59 ms and inter-token latency from 2.41 ms to 1.35 ms with identical outputs. Separately, sglang cut v0.5.20 with 713 PRs from 237 contributors and added GLM-5.3-Flash and Hy4-Pr...

Quick answers

What shipped in Local LLMs on September 19, 2026?
Ollama made per-model reasoning controls discoverable through its API, llama.cpp pushed more architectures and Hexagon kernels through CI, and vLLM added back-pressure detection to its KV cache tiering manager. In total, 119 commits, 119 pull requests, and 12 releases landed.
Who contributed to Local LLMs on September 19, 2026?
14 developers shipped this update, including pdevine, ParthSareen, ServeurpersoCom, shaofeiqi, tboinovski1, bnellnm, frida-andersson, and hmellor, and 6 more.
What were the notable Local LLMs updates?
api: expose model thinking levels and defaults, [KV Offloading] Back-pressure detection and remediation, and hexagon: support for HMX flash-attention head_dim not multiple of 64.