llama.cpp has released version b11002, expanding its pre-built binary support to include CUDA 13 and ROCm 10.0. The release provides separate builds for CUDA 12 and CUDA 13 on both x64 and arm64 Linux/Windows platforms, allowing users with newer NVIDIA hardware to utilize the latest drivers without compilation. Additionally, ROCm 10.0 binaries are now available for Ubuntu and Windows, broadening AMD GPU compatibility. The update also includes OpenVINO and SYCL builds, while macOS Apple Silicon KleidiAI support is currently disabled in this release.
Read originalThis release patches a critical remote code execution vulnerability in the llama.cpp server that allowed unauthenticated attackers to hijack memory via dangling pointers. The flaw stemmed from caching compute graphs that referenced freed buffers, enabling heap corruption and arbitrary code execution through subsequent tensor commands. By discarding cached graphs when buffers are freed, the fix forces a safe fallback to full recomputation without changing the API. This is a vital security update for anyone running the llama.cpp server remotely, closing a direct path to system compromise.
A copy-paste error in llama.cpp was corrupting matrix transpositions on Spacemit hardware, causing significant data corruption for int16 operations. This release patches the specific RVV instruction call to ensure correct computation on these RISC-V based chips. While niche, it prevents silent inference failures for users relying on this specific accelerator architecture. The update also ships binaries for CUDA 13 and ROCm 10.0, keeping the runtime current with latest driver ecosystems.
llama.cpp now runs the DFM Mimir 1B model, a rare example of a hierarchical recurrent transformer that alternates between two distinct processing cycles. This isn't just another standard decoder; it requires handling aliased cache slots and looped graph builds, pushing the runtime's architectural flexibility further than usual. While the decode speed is roughly four times slower than a dense model of similar width due to these 128 block passes, local inference for this specific architecture was previously impossible on consumer hardware. This release effectively opens the door for experimenting with non-standard transformer topologies in open-source environments.
This release targets the friction points that make local AI coding feel fragile. The most critical fix addresses MCP servers timing out after five minutes regardless of configuration, a major blocker for complex agent workflows. Session reliability also improves with self-healing corrupted transcripts and better handling of background agents during resumption. While not feature-heavy, these patches stabilize the environment for developers relying on long-running automated tasks.
© GitHub ChangelogGitHub Enterprise Cloud finally addresses the friction of manual SSO authorization for classic tokens and SSH keys. Admins can now delegate bulk authorization to GitHub Apps via a new API, handling up to 50 organizations in one request without exposing secrets. This shift from manual per-org clicks to automated delegation reduces the temptation to use insecure long-lived tokens. It is a practical infrastructure improvement that streamlines credential rotation for large enterprises managing complex access controls.
© GitHub ChangelogGitHub finally aligns its SCIM implementation with RFC 7643 by adding the profileUrl attribute to user responses. This small but necessary change eliminates the need for identity providers to perform extra lookups or infer account links when provisioning access. The update is additive, meaning existing integrations remain unaffected while new ones can now rely on a standardized field. It’s a quiet fix that reduces friction for enterprise IT teams managing GitHub access at scale.