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Trending or useful GitHub repos / working software

Compute & powerThe Stack

SGLang ships day-zero MoE kernels faster than most teams pick a runtime

Apache-2.0 serving framework. v0.5.14 landed 26 June 2026 with DeepSeek-V4 and Waterfill/LPLB load balancing.

TLDR

SGLang is an open-source LLM and multimodal serving runtime from the sgl-project, hosted under LMSYS. Release v0.5.14 on 26 June 2026 added GLM-5.2, Kimi-K2.7-Code, Waterfill/LPLB MoE dispatch, and DeepSeek-V4 NVFP4 paths documented in release notes. LICENSE is Apache-2.0. GitHub star count at publication is UNKNOWN.

ModelsThe Stack

SAM 3.1 multiplexes video objects; license is Meta SAM, not Apache

27 March 2026 checkpoints on Hugging Face `facebook/sam3.1`. Meta reports ~7x at 128 objects on one H100 versus SAM 3. Weights gated. GitHub stars UNKNOWN.

TLDR

Meta's `facebookresearch/sam3` repo dated 27 March 2026 released SAM 3.1 Object Multiplex and new checkpoints. `RELEASE_SAM3p1.md` reports about 7x speedup at 128 objects on a single H100 versus the SAM 3 November 2025 release, and VOS gains on 6 of 7 named benchmarks. `LICENSE` is the SAM License dated 19 November 2025, a limited non-exclusive grant with trade-control and no-reverse-engineering clauses, not Apache-2.0. Hugging Face `facebook/sam3.1` is the checkpoint host. Independent speed reproduction is UNKNOWN.

ModelsThe Stack

MedGemma 1.5 4B adds CT, MRI, and slide patches under HAI-DEF terms

Google Research, 13 January 2026. Weights are not Apache-2.0. Clinical diagnosis is out of intended use. Internal accuracy deltas are Google's.

TLDR

Google Research posted MedGemma 1.5 4B on 13 January 2026 as an update to MedGemma 1 4B, expanding CT/MRI volumes, whole-slide histopathology patches, longitudinal chest X-rays, anatomical boxes, and lab-report extraction. The model card says use is governed by the Health AI Developer Foundations terms, last modified 15 November 2024: recipe and inference code Apache-2.0, weights and derivatives under HAI-DEF, with a ban on uses that could make Google a medical-device manufacturer. Outputs are not intended to inform diagnosis. Benchmark gains cited in the research blog are Google's internal figures.