llama.cpp's 8 September prerelease sequence now runs through b10867. Later tags recover a reported Vulkan prompt-processing regression, fix Metal quantized-model widths, protect recurrent checkpoint eviction and disable automatic lazy tensor loading on integrated GPUs after a regression.
Why it matters: These late same-day tags change the risk profile of the existing backend release: they add corrective performance and state-management work while reverting an optimization that regressed integrated-GPU behavior.
Artificial Analysis measured API prices of $0.14 per million input tokens and $0.28 per million output tokens for DeepSeek V4-Flash, with an average benchmark-run cost near $0.03 and an Intelligence Index score of 50.
Why it matters: The useful competition is shifting from highest benchmark score toward acceptable completed work at radically lower cost.
DeepSeek released V4-Pro and V4-Flash in preview with open weights, one-million-token context, thinking and non-thinking modes, and OpenAI- and Anthropic-compatible APIs. Pro used a 1.6T-parameter MoE with 49B active parameters, while Flash used 284B total and 13B active parameters for lower-cost serving.
Why it matters: The release gives developers an open-weight, API-compatible alternative spanning a large reasoning/coding tier and a smaller workhorse. Compatible interfaces lower switching cost and make model routing or self-hosted fallback more practical.