Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Flash (High)
71
Qwen3.6-27B
73
Verified leaderboard positions: DeepSeek V4 Flash (High) #23 · Qwen3.6-27B #18
Pick Qwen3.6-27B if you want the stronger benchmark profile. DeepSeek V4 Flash (High) only becomes the better choice if coding is the priority or you need the larger 1M context window.
Agentic
+3.9 difference
Coding
+1.6 difference
Knowledge
+5.0 difference
DeepSeek V4 Flash (High)
Qwen3.6-27B
$0.14 / $0.28
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick Qwen3.6-27B if you want the stronger benchmark profile. DeepSeek V4 Flash (High) only becomes the better choice if coding is the priority or you need the larger 1M context window.
Qwen3.6-27B has the cleaner provisional overall profile here, landing at 73 versus 71. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6-27B's sharpest advantage is in knowledge, where it averages 62.2 against 57.2. The single biggest benchmark swing on the page is HLE, 29.4% to 24%. DeepSeek V4 Flash (High) does hit back in coding, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Flash (High) 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 (High) gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
Qwen3.6-27B is ahead on BenchLM's provisional leaderboard, 73 to 71. The biggest single separator in this matchup is HLE, where the scores are 29.4% and 24%.
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 62.2 versus 57.2. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
DeepSeek V4 Flash (High) has the edge for coding in this comparison, averaging 72.2 versus 70.6. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 55.4. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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