Unverified50% confidenceFactExact time
The Ouro model retains an independent KV cache in each loop, causing the cache size to grow linearly with the number of loops.
1
Sources
50%
Confidence
Long-term
Relevance
11/4/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe memory usage of the KV cache grows linearly with context length, and each concurrent request and each sequence maintains an independent cache.72% similarUnverifiedThe KV cache introduced by extremely long contexts grows linearly with context length, and Unsloth's optimized offload planner prioritizes keeping the KV cache on the GPU.68% similarUnverifiedIn autoregressive inference, the memory footprint of the KV cache grows linearly with sequence length and may equal or exceed the weight volume in long-context scenarios.67% similarUnverifiedThe KV cache grows continuously with sequence length, delivering powerful long-range retrieval capability at the cost of memory that cannot be digested into the model itself.67% similarUnverifiedKV-shareability means that in some trained recurrent models, the KV cache from the last loop can be directly reused by the earlier loops with almost no impact on quality.65% similar
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