Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7
93
DeepSeek V3
38
Verified leaderboard positions: Claude Opus 4.7 #2 · DeepSeek V3 unranked
Pick Claude Opus 4.7 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
+33.7 difference
Knowledge
+1.8 difference
Claude Opus 4.7
DeepSeek V3
$5 / $25
$0.27 / $1.1
N/A
N/A
N/A
N/A
1M
128K
Pick Claude Opus 4.7 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 Opus 4.7 is clearly ahead on the provisional aggregate, 93 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7's sharpest advantage is in coding, where it averages 72.9 against 39.2. The single biggest benchmark swing on the page is SWE-bench Verified, 87.6% to 42%. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 22.7x on output cost alone. Claude Opus 4.7 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.
Claude Opus 4.7 is ahead on BenchLM's provisional leaderboard, 93 to 38. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 87.6% and 42%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 68.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Opus 4.7 has the edge for coding in this comparison, averaging 72.9 versus 39.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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