Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
61
Qwen3.5-35B-A3B
56
Verified leaderboard positions: GPT-5.4 nano unranked · Qwen3.5-35B-A3B #18
Pick GPT-5.4 nano if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+7.7 difference
Knowledge
+26.1 difference
GPT-5.4 nano
Qwen3.5-35B-A3B
$0.2 / $1.25
$0 / $0
191 t/s
N/A
3.64s
N/A
400K
262K
Pick GPT-5.4 nano if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.4 nano is clearly ahead on the provisional aggregate, 61 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. GPT-5.4 nano gives you the larger context window at 400K, compared with 262K for Qwen3.5-35B-A3B.
GPT-5.4 nano is ahead on BenchLM's provisional leaderboard, 61 to 56. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 39% and 54.5%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 53.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for agentic tasks in this comparison, averaging 50.6 versus 42.9. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
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