Make local LLM inference faster with chunk-level KV cache reuse
GitHub repository with 25 stars and 0 forks.
Language: Python
Topics: kv-cache, kv-cache-lp, llm, llm-inference, llm-optimization, local-ai, local-ai-llm, local-llm, open-llm
2026-06-05: 25 stars and 0 forks.
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
GitHub repository with 8,422 stars and 1,246 forks.
Trending score: 2.17; stars gained: +11; forks gained: +6.
Language: Python
Topics: amd, cuda, fast, inference, kv-cache, llm
KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.
GitHub repository with 242 stars and 9 forks.
Trending score: 1.14; stars gained: +14; forks gained: +1.
Language: Python
Topics: agentic-ai, kv-cache, llm, llm-inference, long-context, quantization
Extreme weight + KV cache compression for LLMs on Apple Silicon (MLX implementation of Google's TurboQuant)
GitHub repository with 41 stars and 10 forks.
Trending score: 0.48; stars gained: +2; forks gained: +0.
Language: Python
Topics: apple-silicon, kv-cache, llm, mlx, quantization, turboquant
Extend LLM context windows beyond GPU memory limits with disk-backed KV cache.
GitHub repository with 11 stars and 0 forks.
Trending score: 0.31; stars gained: +1; forks gained: +0.
Language: Python
Topics: ai, cache, deepseek, disk-cache, gpu, inference
🤖🗜️⚡️ Local LLM server for Apple Silicon. 5.4× faster end-to-end on long contexts vs Ollama, 33% less RAM, INT3 support for Qwen3. OpenAI + Ollama drop-in. Built for repeated long-context workloads on memory-constrained Macs.
GitHub repository with 7 stars and 0 forks.
Trending score: 0.07; stars gained: +0; forks gained: +0.
Language: Python
Topics: apple-silicon, llm, local-ai, local-llm, macos, mlx
Official Pytorch Code of the Paper "FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization"
GitHub repository with 240 stars and 12 forks.
Trending score: 0.03; stars gained: -1; forks gained: +0.
Language: Python
Topics: dmd, fashion, garment-switch, interactive, kv-cache, real-time
The agent that grows with you
GitHub repository with 181,783 stars and 31,190 forks.
Trending score: 5.95; stars gained: +1,867; forks gained: +361.
Language: Python
Topics: ai, ai-agent, ai-agents, anthropic, chatgpt, claude
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
GitHub repository with 13,361 stars and 853 forks.
Trending score: 5.69; stars gained: +2,829; forks gained: +175.
Language: Python
Topics: agent, ai, anthropic, compression, context-engineering, context-window
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GitHub repository with 27,484 stars and 2,256 forks.
Trending score: 5.52; stars gained: +1,079; forks gained: +89.
Language: Python
Topics: academic-pipeline, academic-writing, ai-research, claude, claude-code, literature-review
Learn it. Build it. Ship it for others.
GitHub repository with 28,622 stars and 4,680 forks.
Trending score: 5.32; stars gained: +1,261; forks gained: +238.
Language: Python
Topics: agents, ai, ai-agents, ai-engineering, computer-vision, course
GitHub repository with 30,029 stars and 4,231 forks.
Trending score: 4.88; stars gained: +688; forks gained: +114.
Language: Python
Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.
GitHub repository with 4,250 stars and 534 forks.
Trending score: 4.88; stars gained: +476; forks gained: +68.
Language: Python
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
GitHub repository with 8,422 stars and 1,246 forks.
Trending score: 2.17; stars gained: +11; forks gained: +6.
Language: Python
Topics: amd, cuda, fast, inference, kv-cache, llm
KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.
GitHub repository with 242 stars and 9 forks.
Trending score: 1.14; stars gained: +14; forks gained: +1.
Language: Python
Topics: agentic-ai, kv-cache, llm, llm-inference, long-context, quantization
Extreme weight + KV cache compression for LLMs on Apple Silicon (MLX implementation of Google's TurboQuant)
GitHub repository with 41 stars and 10 forks.
Trending score: 0.48; stars gained: +2; forks gained: +0.
Language: Python
Topics: apple-silicon, kv-cache, llm, mlx, quantization, turboquant
Object-storage-native KV cache for LLM inference & RL. Cross-restart, cross-conversation, cross-engine via shared S3 bucket.
GitHub repository with 12 stars and 1 forks.
Trending score: 0.33; stars gained: +1; forks gained: +0.
Language: Rust
Topics: amd, caching, ds4, inference, kv-cache, llm
Extend LLM context windows beyond GPU memory limits with disk-backed KV cache.
GitHub repository with 11 stars and 0 forks.
Trending score: 0.31; stars gained: +1; forks gained: +0.
Language: Python
Topics: ai, cache, deepseek, disk-cache, gpu, inference
🤖🗜️⚡️ Local LLM server for Apple Silicon. 5.4× faster end-to-end on long contexts vs Ollama, 33% less RAM, INT3 support for Qwen3. OpenAI + Ollama drop-in. Built for repeated long-context workloads on memory-constrained Macs.
GitHub repository with 7 stars and 0 forks.
Trending score: 0.07; stars gained: +0; forks gained: +0.
Language: Python
Topics: apple-silicon, llm, local-ai, local-llm, macos, mlx