Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
36
GPT-5.4 mini
71
Pick GPT-5.4 mini if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Knowledge
+12.6 difference
DeepSeek V3
GPT-5.4 mini
$0.27 / $1.1
$0.75 / $4.5
N/A
201 t/s
N/A
3.85s
128K
400K
Pick GPT-5.4 mini if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.4 mini is clearly ahead on the provisional aggregate, 71 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 4.1x on output cost alone. GPT-5.4 mini is the reasoning model in the pair, while DeepSeek V3 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. GPT-5.4 mini gives you the larger context window at 400K, compared with 128K for DeepSeek V3.
GPT-5.4 mini is ahead on BenchLM's provisional leaderboard, 71 to 36. The biggest single separator in this matchup is GPQA, where the scores are 59.1% and 88%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 57.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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