Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3.2
56
Hy3 Preview
59
Pick Hy3 Preview if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+0.9 difference
DeepSeek V3.2
Hy3 Preview
$0.28 / $0.42
$0 / $0
35 t/s
N/A
3.75s
N/A
128K
256K
Pick Hy3 Preview if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Hy3 Preview has the cleaner provisional overall profile here, landing at 59 versus 56. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek V3.2 is also the more expensive model on tokens at $0.28 input / $0.42 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Hy3 Preview. That is roughly Infinityx on output cost alone. Hy3 Preview 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. Hy3 Preview gives you the larger context window at 256K, compared with 128K for DeepSeek V3.2.
Hy3 Preview is ahead on BenchLM's provisional leaderboard, 59 to 56.
DeepSeek V3.2 has the edge for coding in this comparison, averaging 60.9 versus 60. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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