DeepSeek V4 Flash (0731)

Key strengths. The model's defining feature is its hybrid thinking/non-thinking design: callers can dial reasoning effort up or down per request rather than always paying for maximum deliberation. It is built and documented around agentic and coding reasoning workloads, and Stav's routing signals rate it strongest on code, with agentic tasks well behind. Its context window — over a million tokens — lets it hold entire codebases, long transcripts, or multi-document research sets in a single call.

When to use it. Use this model for coding and agentic tasks that benefit from adjustable reasoning depth, such as multi-step debugging, code review across a large repository, or research synthesis over long documents. Its fast initial response times and strong coding benchmark scores make it a reasonable default for reasoning-heavy work where you don't need a flagship-tier model for every request. Reach for the high or max reasoning-effort setting when task complexity justifies the extra generation time, and low effort for routine, lower-stakes calls.