Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (Max)
77
Qwen3.6-27B
75
Verified leaderboard positions: DeepSeek V4 Flash (Max) #12 · Qwen3.6-27B #13
Pick DeepSeek V4 Flash (Max) if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+4.0 difference
Coding
+3.1 difference
Knowledge
+2.2 difference
DeepSeek V4 Flash (Max)
Qwen3.6-27B
$0.14 / $0.28
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick DeepSeek V4 Flash (Max) if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
DeepSeek V4 Flash (Max) has the cleaner provisional overall profile here, landing at 77 versus 75. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
DeepSeek V4 Flash (Max)'s sharpest advantage is in agentic, where it averages 63.3 against 59.3. The single biggest benchmark swing on the page is HLE, 34.8% to 24%. Qwen3.6-27B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Flash (Max) is also the more expensive model on tokens at $0.14 input / $0.28 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. DeepSeek V4 Flash (Max) gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
DeepSeek V4 Flash (Max) is ahead on BenchLM's provisional leaderboard, 77 to 75. The biggest single separator in this matchup is HLE, where the scores are 34.8% and 24%.
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 62.2 versus 60. Inside this category, HLE is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (Max) has the edge for coding in this comparison, averaging 73.7 versus 70.6. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (Max) has the edge for agentic tasks in this comparison, averaging 63.3 versus 59.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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