Releases like Spark-X2.5, MiniCPM5-2B, K2-Horizon-MoVA and Qwen-Drive bring compact or sparse open models with lower active parameters and specialized capabilities. llama.cpp is adding support for new architectures such as Tencent Hy4, reinforcing local, edge and on-premise inference paths.
Qwen has published an open-weight model derived from a 4B checkpoint and fine-tuned for driving. The full BF16 checkpoint is 9B. It signals Chinese labs pushing toward autonomous driving with open models, with implications for local inference, data s...
OpenBMB has released MiniCPM5-2B, a 2-billion-parameter open weights model scoring 15 on the Artificial Analysis Intelligence Index v4.2, the highest among open models up to 4B. For self-hosted deployments, the small size and open weights lower the p...
A llama.cpp pull request adds support for Spark-X2.5, two compact 4B and 1.7B parameter LLMs with a native context window of up to 1M tokens and a hybrid sliding-window attention architecture. The move lowers the barrier for local and self-hosted inf...
Pull request #28127, adding Hy4-preview support to llama.cpp, brings no benchmarks but signals convergence in the self-hosted ecosystem. Even cloud vendors are paying attention to on-premise pipelines. Stability, licensing, and documentation remain o...
Pull request #28127 adds support for the Tencent Hy4 preview architecture in llama.cpp. A concrete signal for teams evaluating on-premise stacks and data sovereignty, with no official benchmarks.
IFM has published the final checkpoint of the sparse Mixture-of-Experts model K2-Horizon-MoVA-36B-A4B, with 36 billion total parameters and 4 billion active per token. Released in GGUF format, it competes on agentic and reasoning tasks with closed fr...
