Concise monthly summary for February 2026 highlighting delivered features, fixed issues, and overall impact. The work focused on enhancing LLM inference workflows, expanding modality support, and improving UI content handling in the ggml-org/llama.cpp project.

January 2026 (2026-01) monthly summary for ggml-org/llama.cpp: Delivered features to boost adaptability and real-time capabilities, fixed a critical ASR issue, and expanded embedding options. Key features delivered include optional input normalization for LFM2-VL, a new LFM2-ColBert-350M embedding dimension exposed via llama_model_n_embd_out(), and a streaming ISTFT implementation enabling real-time audio output with per-instance caches and a unified FFT/IFFT pipeline. Major bug fix: ASR chain for LFM2.5-Audio-1.5B corrected by removing an unnecessary input-processing callback. Overall impact: enhanced model flexibility, lower latency for streaming scenarios, and more robust ASR workflows, enabling easier deployment and higher-quality outputs. Technologies/skills demonstrated: advanced C++ engineering, real-time DSP pipelines (ISTFT, FFT/IFFT), per-instance caching, modular parameter exposure, and conditional normalization features.

December 2025 monthly summary for ggml-org/llama.cpp: The month focused on stabilizing the LFM2_MOE pathway through a critical tensor-naming fix, ensuring correct runtime behavior and integration. No new features were released this month; primary effort was bug resolution and code quality improvements to support reliable inference in the LFM2_MOE architecture.

November 2025 monthly summary focused on delivering higher-quality image upscaling for LFM2-VL and improving stability and performance across two major GGML repositories (ggml-org/ggml and ggml-org/llama.cpp).

October 2025 performance summary for ggml-org/llama.cpp. Focused on delivering model support and improving maintainability. Highlights include enabling LiquidAI LFM2-MoE hybrid model support and updates to conversion scripts and internal structures to support Mixture of Experts. PR feedback addressed; code quality improvements implemented (e.g., removal of defaultdict). No separate bug fixes logged this month; emphasis on feature delivery and upstream collaboration.

August 2025 monthly summary focusing on delivering LFM2 model enhancements in llama.cpp with untied embeddings and increased image token capacity. Documentation updates accompany the feature, reflecting the change set and improving maintainability.

July 2025 performance summary focusing on delivering reliable LFM2 support in llama.cpp, with documentation updates, parallel processing fixes, and expanded test coverage for ssm_conv. The work emphasizes business value through improved multi-sequence processing reliability, faster onboarding, and stronger test discipline.