Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 5
94
DeepSeek V3
35
Pick Claude Sonnet 5 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.
Coding
+24.0 difference
Knowledge
+12.6 difference
Claude Sonnet 5
DeepSeek V3
$3 / $15
$0.27 / $1.1
N/A
N/A
N/A
N/A
1M
128K
Pick Claude Sonnet 5 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.
Claude Sonnet 5 is clearly ahead on the provisional aggregate, 94 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Sonnet 5's sharpest advantage is in coding, where it averages 63.2 against 39.2. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 5 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 13.6x on output cost alone. Claude Sonnet 5 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. Claude Sonnet 5 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.
Claude Sonnet 5 is ahead on BenchLM's provisional leaderboard, 94 to 35.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 57.4. Claude Sonnet 5 stays close enough that the answer can still flip depending on your workload.
Claude Sonnet 5 has the edge for coding in this comparison, averaging 63.2 versus 39.2. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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