Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
62
Qwen3.6-35B-A3B
64
Verified leaderboard positions: GPT-5.4 nano unranked · Qwen3.6-35B-A3B #13
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
Agentic
+8.6 difference
Knowledge
+7.3 difference
Multimodal
+9.2 difference
GPT-5.4 nano
Qwen3.6-35B-A3B
$0.2 / $1.25
N/A
191 t/s
N/A
3.64s
N/A
400K
262K
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
Qwen3.6-35B-A3B has the cleaner provisional overall profile here, landing at 64 versus 62. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6-35B-A3B's sharpest advantage is in multimodal & grounded, where it averages 75.3 against 66.1. The single biggest benchmark swing on the page is HLE, 37.7% to 21.4%.
GPT-5.4 nano gives you the larger context window at 400K, compared with 262K for Qwen3.6-35B-A3B.
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 64 to 62. The biggest single separator in this matchup is HLE, where the scores are 37.7% and 21.4%.
Qwen3.6-35B-A3B has the edge for knowledge tasks in this comparison, averaging 60.5 versus 53.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.6-35B-A3B has the edge for agentic tasks in this comparison, averaging 51.5 versus 42.9. Inside this category, Toolathlon is the benchmark that creates the most daylight between them.
Qwen3.6-35B-A3B has the edge for multimodal and grounded tasks in this comparison, averaging 75.3 versus 66.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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