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billion-context releases plugin for long-running coding agents

AI summary

The billion-context project introduced an installable context-compression plugin for prolonged coding-agent sessions, distributed through npm as “billion-context.” Its GitHub description says the plugin uses model-driven, reversible compression between clients and model APIs, while claiming fivefold token savings, a 95–97% prefix-cache hit rate, and compression overhead of no more than 2%; these figures lack independent verification in the supplied report.

In-depth insight

The plugin targets a central constraint on long-running coding agents by compressing conversation history rather than relying on a hard context-window limit.

A context-compression plugin for month-long single sessions (billions of tokens) ,small context windows (a 100K context is enough) and token savings (5x fewer tokens) .上下文压缩插件,月级长会话会话, 兼顾小窗口(100k上下文足矣)省token(省5倍token) . billion-context is all you need


billion-context

English | 中文

Context-compression plugin — billion-context is all you need.

small context windows (100K is enough) · 5× fewer tokens · month-long single sessions (billions of tokens) · high compression quality

Some source content is omitted. Continue reading on the original site.

#billion-context#Anthropic#OpenAI#DeepSeek V4.1 Flash#Qwen3-Embedding-8B#Qwen3-Reranker-4B#Pi Agent

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