Blog
Updates on our LLM compression models and technology.
Cut Your LLM API Costs by 70% Without Losing Quality
A practical framework for reducing LLM API costs across system prompts, conversation history, RAG context, tool schemas, and output. Real pricing math included.
May 2026
GuideWhy Your RAG App's Token Bill Is So High (And How to Fix It)
Most RAG applications over-fetch context by 3-5x. Break down where your retrieval tokens go and how compression, reranking, and chunk hygiene cut costs.
May 2026
Case StudyOne of the biggest token consumers globally improved quality by removing context bloat
Processing 193B tokens/month, Pax Historia ran a 268K-vote model arena with bear-1.1 compression. Compressed models scored higher and A/B tests showed +5% purchase amount lift.
February 2026
NewIntroducing bear-1.1: Improved LLM Compression
bear-1.1 is the latest compression model from The Token Company. An improved version of bear-1 with better accuracy preservation and faster compression speeds.
February 2026
Modelbear-1: First LLM Input Compression Model
bear-1 compresses LLM input tokens by 66% without sacrificing accuracy. Learn how semantic compression reduces AI costs by 3x.
November 2025