FrontierThe story, in brief
The KV Cache Compression Race: TurboQuant vs OSCAR vs EpiCache
KV cache now outweighs model weights. Here's how TurboQuant, OSCAR, and EpiCache are solving the long-context memory bottleneck.
The KeyNews take
Why it matters
As context windows expand, KV cache memory has become the primary constraint on inference efficiency. Three competing approaches are emerging to compress this bottleneck—and understanding their trade-offs is critical for anyone deploying long-context models at scale.
The key facts
4 to knowKV cache memory now exceeds model weight memory at long context lengths
Three main compression techniques competing: TurboQuant, OSCAR, EpiCache
Techniques characterized as complementary rather than directly competitive
Published June 18, 2026 — recent technical landscape
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MarkTechPostmarktechpost.com
Publisher excerpt: The KV cache now outweighs model weights at long context. Here's how TurboQuant, OSCAR, and EpiCache each attack that memory bottleneck — and why they're more complementary than competitive.