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Source channel @githubtrending · Post #15431 · Jan 23

#cplusplus#3d_engine#arm64#cmake#cplusplus#cpp17#d3d11#directx#directx11#engine#game#game_engine#gamedev#mod#opengl#opensource#sdl#sdl2#stalker#x64#xray_engine OpenXRay is a free, improved version of the X-Ray Engine for S.T.A.L.K.E.R. games like Call of Pripyat and Clear Sky. It adds 64-bit support, higher FPS, bug fixes, modding tools, and runs on Linux, macOS, and more. This benefits you with smoother, more stable gameplay, better performance on modern or non-Windows PCs, and easy access to new mods without changing the classic feel. https://github.com/OpenXRay/xray-16

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Machinelearning

@ai_machinelearning_big_data · Post #8680 · 10/02/2025, 05:01 PM

✔️IBM представила Granite 4.0 — новое семейство open-weights языковых моделей от 3B до 32B параметров. Четыре новые модели: - Granite 4.0 H Small - 32B/9B активных параметров - Granite 4.0 H Tiny - 7B/1B - Granite 4.0 H Micro - 3B/3B - Granite 4.0 Micro - 3B/3B Benchmarking (Artificial Analysis Index): - Granite 4.0 H Small: 23 балла (на 8 выше Granite 3.3 8B), обходит Gemma 3 27B (22), но уступает Mistral Small 3.2 (29) и Qwen3 30B A3B (37). - Granite 4.0 Micro: 16 баллов, выше Gemma 3 4B (15) и LFM 2 2.6B (12). ⚡ Token efficiency: - Granite 4.0 Small — 5.2M токенов - Granite 4.0 Micro — 6.7M токенов Обе модели заметно эффективнее Granite 3.3 8B и большинства non-reasoning моделей <40B. Детали: - Контекст: до 128K токенов - Лицензия: Apache 2.0 - Granite 4.0 H Small доступна на Replicate по $0.06 / $0.25 за 1M input/output токенов - Все модели доступны на Hugging Face - Модель Micro (3.4B) можно запускать полностью локально. 🔗 Hugging Face: https://huggingface.co/collections/unsloth/granite-40-68ddf64b4a8717dc22a9322d 🔗Unsloth: https://docs.unsloth.ai/new/ibm-granite-4.0 @ai_machinelearning_big_data #AI#IBM#Granite4#LLM#OpenWeights

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@githubtrending · Post #15348 · 12/20/2025, 12:00 PM

#go#gemma3#go#gpt_oss#granite4#llama#llama3#llm#on_device_ai#phi3#qwen3#qwen3vl#sdk#stable_diffusion#vlm NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience. https://github.com/NexaAI/nexa-sdk