Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 4.6
84
DeepSeek V4 Pro (Max)
87
Verified leaderboard positions: Claude Sonnet 4.6 unranked · DeepSeek V4 Pro (Max) #2
Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. Claude Sonnet 4.6 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+8.7 difference
Coding
+9.5 difference
Knowledge
+7.6 difference
Claude Sonnet 4.6
DeepSeek V4 Pro (Max)
$3 / $15
$1.74 / $3.48
44 t/s
N/A
1.48s
N/A
200K
1M
Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. Claude Sonnet 4.6 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeek V4 Pro (Max) has the cleaner provisional overall profile here, landing at 87 versus 84. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek V4 Pro (Max)'s sharpest advantage is in coding, where it averages 75.9 against 66.4. The single biggest benchmark swing on the page is HLE, 49% to 37.7%. Claude Sonnet 4.6 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 4.6 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $1.74 input / $3.48 output per 1M tokens for DeepSeek V4 Pro (Max). That is roughly 4.3x on output cost alone. DeepSeek V4 Pro (Max) is the reasoning model in the pair, while Claude Sonnet 4.6 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. DeepSeek V4 Pro (Max) gives you the larger context window at 1M, compared with 200K for Claude Sonnet 4.6.
DeepSeek V4 Pro (Max) is ahead on BenchLM's provisional leaderboard, 87 to 84. The biggest single separator in this matchup is HLE, where the scores are 49% and 37.7%.
Claude Sonnet 4.6 has the edge for knowledge tasks in this comparison, averaging 73.7 versus 66.1. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (Max) has the edge for coding in this comparison, averaging 75.9 versus 66.4. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro (Max) has the edge for agentic tasks in this comparison, averaging 74 versus 65.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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