Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 4.6
83
DeepSeek V3
36
Pick Claude Sonnet 4.6 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you want the cheaper token bill.
Coding
+27.2 difference
Knowledge
+3.7 difference
Claude Sonnet 4.6
DeepSeek V3
$3 / $15
$0.27 / $1.1
44 t/s
N/A
1.48s
N/A
200K
128K
Pick Claude Sonnet 4.6 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you want the cheaper token bill.
Claude Sonnet 4.6 is clearly ahead on the provisional aggregate, 83 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Sonnet 4.6's sharpest advantage is in coding, where it averages 66.4 against 39.2. The single biggest benchmark swing on the page is SWE-bench Verified, 79.6% to 42%.
Claude Sonnet 4.6 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 4.6 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.
Claude Sonnet 4.6 is ahead on BenchLM's provisional leaderboard, 83 to 36. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 79.6% and 42%.
Claude Sonnet 4.6 has the edge for knowledge tasks in this comparison, averaging 73.7 versus 70. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Sonnet 4.6 has the edge for coding in this comparison, averaging 66.4 versus 39.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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