Step 3.5 Flash dramatically improves performance with 75% less memory overhead for large context windows in llama.cpp

Step 3.5 Flash now maintains only 2.5x performance slowdown at 170k context compared to previous 3x slowdown at 96k context

Context memory usage reduced by 75%, enabling users to run larger quantizations like Q4_K_L with up to 220k context window

Performance benchmarks on RTX 5090 + RTX PRO 6000 show sustained 75 tokens/sec at 170k context versus 45 tokens/sec previously

Improved model support makes Step 3.5 Flash significantly more practical for AI agents, Cline, and context-intensive orchestrators

Users can now choose between higher quality quantizations or parallel request processing while maintaining reasonable performance