RTX 5070 Ti Laptop 12GB 跑 Qwen3.8-27B:NInfer + KVMem、256K 逻辑上下文、RAM KV、MTP、快速缓存续接与 dsh 本地 Agent / 搜索 / 浏览器。含源码、Windows 部署及实测。
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
High-performance open-source in-memory graph database for GraphRAG, AI memory, agentic AI, and real-time graph analytics. Cypher-compatible, built in C++.
An alternative Windows context menu, and more.
The ripgrep of AI context: a zero-dependency C++23 CLI + MCP server for coding agents. Find what you want without reading the repo, then check you built what you meant — blast radius, tests-to-run, quality deltas. Signatures at 74.7% fewer bytes than bodies; every guess labelled, every loss published. Paddle out with a map.
The Fastest Unified Streaming SQL Engine in a Single C++ Binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute real-time context from streams, logs, metrics, events, and CDC.
A cross-platform context-aware key remapper.
KVMem virtualizes KV memory across inference backends to make ultra-long-context local AI accessible on limited hardware.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to control Unreal Engine through the native C++ Automation Bridge plugin. Built with TypeScript and C++.
Unreal Engine Vibe Coding tool
Context Free is a program that generates images from written instructions called a grammar. The program follows the instructions in a few seconds to create images that can contain millions of shapes.
The efficient SMT-based context-bounded model checker (ESBMC)
llama.cpp fork for significantly improved performance on Ampere (especially RTX 3090 / 3090 Ti): example: 95+ tok/s over a 100K-token generation at temperature 1 for qwen3.8, supporting full 262K ctx. Supports low memory (12gb) configs for 200k+ ctx
为 Windows 11 新版右键菜单打造的原生 7-Zip 扩展体验
Native Windows port of NInfer engine for RTX 5090. Features Qwen3.8-27B with QUASAR and NInfer models, MTP/DFlash2 with vision and 262,144 context
LLM inference engine written from scratch in HIP for AMD Strix Halo (gfx1151) and Qwen3.8-Flash-Next - ~50 tokens/s out to 492k context
llama.cpp optimized for NVIDIA Tesla V100 (SM70): large MoE Qwen3.8-Flash-Next with MTP (prefill 3464 tok/s at 200K context, 6x V100-16GB) and Qwen3.8-27B with DFlash2 (decode up to 225 tok/s); 2-6 GPUs, 262K-512K context, multimodal, concurrent serving.
FlashPrefill V2: Block-Sparse Prefill Attention for Long-Context LLM Serving
DeepSeek V4 Flash 0731 - free deepseek v4 flash download, gguf, ollama, deepseek v4 pro 0813. deepseek v4 flash vs pro, benchmark, MoE, 1M context, compressed sparse attention, coding. CUDA/CPU, no API key, Windows local AI. Download:🡇