Copium
BetaContext optimization layer for LLMs. 65-90% token savings with zero quality loss.
Copium is a context optimization layer for Large Language Models (LLMs). It acts as a drop-in proxy for major LLMs like Claude, GPT, Gemini, and local models (Ollama/VLLM/llama.cpp). It achieves 65-90% token savings with zero quality loss through features like KV cache-aware compression, session deduplication, error cards, and Pichay-proven context paging. Ideal for reducing API costs and improving efficiency.
Problem
Large Language Models often incur high costs and latency due to inefficient context management, especially with long conversations or complex agentic workflows. Redundant information processing and large context windows lead to significant token consumption, translating into higher API bills and slower application performance. Developers struggle to optimize these aspects without compromising output quality or requiring complex architectural changes, hindering the scalability and cost-effectiveness of LLM-powered applications.
Solution
Copium tackles LLM inefficiency by acting as an intelligent, drop-in proxy. It sits between your application and the LLM, transparently optimizing context requests. Through advanced techniques like KV cache-aware compression and session deduplication, it reduces the actual tokens sent to the LLM by 65-90%. This leads to substantial cost savings and improved inference speeds without any degradation in response quality. It's compatible with cloud LLMs (Claude, GPT, Gemini) and local setups (Ollama, VLLM, llama.cpp).