DeepSeek V4 Pro vs Step 3.7 Flash

Pick Step 3.7 Flash if you want the stronger benchmark profile. DeepSeek V4 Pro only becomes the better choice if coding is the priority or you need the larger 1M context window.

Step 3.7 Flash has the cleaner provisional overall profile here, landing at 72 versus 70. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Step 3.7 Flash's sharpest advantage is in agentic, where it averages 65.9 against 59.1. The single biggest benchmark swing on the page is SWE-bench Pro, 52.1% to 56.3%. DeepSeek V4 Pro does hit back in coding, so the answer changes if that is the part of the workload you care about most.

DeepSeek V4 Pro is also the more expensive model on tokens at $1.74 input / $3.48 output per 1M tokens, versus $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 3.0x on output cost alone. Step 3.7 Flash is the reasoning model in the pair, while DeepSeek V4 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Pro gives you the larger context window at 1M, compared with 256K for Step 3.7 Flash.