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The Wire · Showcase

OLLAMA LAUNCHES DEEPSEEK AND MUSE INTEGRATIONS WHILE VLLM SHIPS HARDWARE-AGNOSTIC MODELING

By RepoJournal · Filed · About Local LLMs

Ollama just opened its launch ecosystem to DeepSeek Harness and Meta's Muse Code, while vLLM pivots to HuggingFace transformers as a unified backend for tail models.

Ollama's launch system now integrates DeepSeek Harness [1] and Muse Code [2], giving developers CLI-native access to these tools with local or cloud Ollama models through a single command. The Harness integration wires web search directly into Ollama's model catalog, while Muse gets its own isolated config root to avoid collision with Meta-backed installs. Meanwhile, Ollama fixed a correctness bug in Muse Glimmer's reasoning template [3], normalizing "Reasoning effort" to "Reasoning strength" and preventing duplicate reasoning directives that could confuse the model. On the vLLM side, the project shipped a hardware-agnostic modeling layer [4] that lets tail models live in HuggingFace transformers and execute through vLLM via the transformers backend, a major shift toward reducing fragmentation across hardware. Performance gains landed across the stack: llama.cpp corrected metric counting [6] to properly track processed vs. cached tokens, SYCL added Q3_K ESIMD kernels and fused unary operations with multiplication for measurable throughput lifts [7] [8], and sglang cut diffusion denoise time by 13.1% on H100 by hoisting rope cache and fusing per-token adaLN operations [9]. Breaking security change: vLLM now enforces audio decode duration limits in NanoNemotronVL [5] to prevent resource exhaustion attacks.

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Action items

References

  1. [1] launch: add DeepSeek Harness integration ↗ ollama/ollama
  2. [2] launch: add Muse Code integration ↗ ollama/ollama
  3. [3] model/renderers: match Muse Glimmer reasoning template ↗ ollama/ollama
  4. [4] Hardware-agnostic model definition via HF transformer backend (1/N) ↗ vllm-project/vllm
  5. [5] fix(security): enforce audio decode duration limit in NanoNemotronVL (#50221) vllm-project/vllm
  6. [6] server: refactor + correctness fixes for metrics ↗ ggml-org/llama.cpp
  7. [7] Add DMMV ESIMD Q3_K kernel ↗ ggml-org/llama.cpp
  8. [8] sycl: fuse UNARY(silu|sigmoid|softplus) + MUL ↗ ggml-org/llama.cpp
  9. [9] [diffusion] Wan2.2-TI2V: fuse per-token adaLN table add into contiguous slices + hoist rope cache (denoise -13.1% H100 / -12.6% H200, bit-exact; eager beats compile) ↗ sgl-project/sglang

Quick answers

What shipped in Local LLMs on August 14, 2026?
Ollama just opened its launch ecosystem to DeepSeek Harness and Meta's Muse Code, while vLLM pivots to HuggingFace transformers as a unified backend for tail models. In total, 125 commits, 125 pull requests, and 11 releases landed.
Who contributed to Local LLMs on August 14, 2026?
16 developers shipped this update, including ParthSareen, dhiltgen, ngxson, arthw, malsbat, Titaniumtown, Zijun Yu, and Juan Pérez de Algaba, and 8 more.
What were the notable Local LLMs updates?
launch: add DeepSeek Harness integration, launch: add Muse Code integration, and model/renderers: match Muse Glimmer reasoning template.

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