Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3.2
56
LongCat-2.0
80
Pick LongCat-2.0 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Coding
+1.4 difference
DeepSeek V3.2
LongCat-2.0
$0.28 / $0.42
$0.75 / $2.95
35 t/s
N/A
3.75s
N/A
128K
1M
Pick LongCat-2.0 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if coding is the priority or you want the cheaper token bill.
LongCat-2.0 is clearly ahead on the provisional aggregate, 80 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
LongCat-2.0 is also the more expensive model on tokens at $0.75 input / $2.95 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 7.0x on output cost alone. LongCat-2.0 is the reasoning model in the pair, while DeepSeek V3.2 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. LongCat-2.0 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.2.
LongCat-2.0 is ahead on BenchLM's provisional leaderboard, 80 to 56.
DeepSeek V3.2 has the edge for coding in this comparison, averaging 60.9 versus 59.5. LongCat-2.0 stays close enough that the answer can still flip depending on your workload.
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