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ISOM-R2: Streaming 1,055,402 Tokens on 3.24 GB Peak VRAM

Community description: Standard Transformer attention has a memory problem at scale. For a 1.05 million-token context with...

Dev.to | Oct 2, 2026 | Prannessh KVA

Automated excerpt

Instead of maintaining a linearly growing KV cache across every token, ISOM-R2 processes context through bounded isometric state projections, keeping GPU memory flat regardless of sequence length. Prefill VRAM Flat at 2. 97 GB across all 1M tokens Memory vs. No token ever materializes a full KV cache entry in GPU memory.

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