Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash
59
o1
58
Verified leaderboard positions: DeepSeek V4 Flash #23 · o1 unranked
Pick DeepSeek V4 Flash if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Knowledge
+30.5 difference
DeepSeek V4 Flash
o1
$0.14 / $0.28
$15 / $60
N/A
98 t/s
N/A
32.29s
1M
200K
Pick DeepSeek V4 Flash if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
DeepSeek V4 Flash finishes one point ahead on BenchLM's provisional leaderboard, 59 to 58. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash. That is roughly 214.3x on output cost alone. o1 is the reasoning model in the pair, while DeepSeek V4 Flash 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 Flash gives you the larger context window at 1M, compared with 200K for o1.
DeepSeek V4 Flash is ahead on BenchLM's provisional leaderboard, 59 to 58. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 75.7%.
o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 45.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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