Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (High)
72
Step 3.7 Flash
72
Verified leaderboard positions: DeepSeek V4 Flash (High) #23 · Step 3.7 Flash unranked
Treat this as a split decision. DeepSeek V4 Flash (High) makes more sense if coding is the priority or you want the cheaper token bill; Step 3.7 Flash is the better fit if agentic is the priority.
Agentic
+10.5 difference
Coding
+15.9 difference
DeepSeek V4 Flash (High)
Step 3.7 Flash
$0.14 / $0.28
$0.2 / $1.15
N/A
N/A
N/A
N/A
1M
256K
Treat this as a split decision. DeepSeek V4 Flash (High) makes more sense if coding is the priority or you want the cheaper token bill; Step 3.7 Flash is the better fit if agentic is the priority.
DeepSeek V4 Flash (High) and Step 3.7 Flash finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
Step 3.7 Flash is also the more expensive model on tokens at $0.20 input / $1.15 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 4.1x on output cost alone. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 256K for Step 3.7 Flash.
DeepSeek V4 Flash (High) and Step 3.7 Flash are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
DeepSeek V4 Flash (High) has the edge for coding in this comparison, averaging 72.2 versus 56.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 65.9 versus 55.4. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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