Relace Compact: Fast Agent Context Compression Model
stuffyokodraws · x · 2026-07-15
To address the soaring costs of expanding agent context in long conversations, Relace introduced Relace Compact, a model designed specifically for context compression.
- Pain Point: Compressing context on cache misses can cut token costs by over 50%, but standard models take 1-2 minutes to self-summarize, severely degrading the experience.
- Solution: Modified for token-level classification tasks, Relace Compact runs at speeds up to 50k tokens/s, costing an order of magnitude less than reading from cache.
- Testing: Long conversation compression that previously took 7 minutes now takes just 5 seconds. Users can enable automatic compression in long chats via a plugin.
Related event: Relace Compact Model Compresses Agent Context in 5 Seconds to Cut Costs(3 posts)→
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