DeepSeek-V4 Million-Token Open-Source Push
Key Questions
What is DeepSeek-V4's context length and key strengths?
DeepSeek-V4 supports 1M token context with Hybrid Attention, mHC, and Muon. It achieves SOTA in open reasoning, coding, and math at trillion-scale. This pushes open-source boundaries.
What are Mistral Medium 3.5's achievements?
Mistral Medium 3.5 is a dense 128B model scoring 77.6% on SWE-Bench. It supports 256k context for agentic tasks. It joins the surge in high-performance open models.
What settings optimize DeepSeek-V4 performance?
In think mode, DeepSeek-V4 does not allow setting temperature or top_p for best performance. Default settings are recommended. This ensures optimal reasoning and coding outputs.
DeepSeek-V4 1M ctx Hybrid Attention/mHC/Muon trillion-scale open SOTA reasoning/coding/math; Mistral Medium 3.5 128B 77.6% SWE-Bench/256k agentic joins surge.
Sources (2)
Updated Apr 30, 2026