Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
59
DeepSeek V3.2
60
Pick DeepSeek V3.2 if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you need the larger 200K context window.
Coding
+12.4 difference
Claude Haiku 4.5
DeepSeek V3.2
$1 / $5
$0 / $0
N/A
35 t/s
N/A
3.75s
200K
128K
Pick DeepSeek V3.2 if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you need the larger 200K context window.
DeepSeek V3.2 finishes one point ahead on BenchLM's provisional leaderboard, 60 to 59. 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.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek V3.2. That is roughly Infinityx on output cost alone. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.2.
DeepSeek V3.2 is ahead on BenchLM's provisional leaderboard, 60 to 59.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 60.9. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.
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