Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 mini
71
Qwen3.5 397B
64
Verified leaderboard positions: GPT-5.4 mini unranked · Qwen3.5 397B #15
Pick GPT-5.4 mini if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+9.4 difference
Knowledge
+7.8 difference
Multimodal
+3.0 difference
GPT-5.4 mini
Qwen3.5 397B
$0.75 / $4.5
$0.6 / $3.6
201 t/s
96 t/s
3.85s
2.44s
400K
128K
Pick GPT-5.4 mini if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.4 mini is clearly ahead on the provisional aggregate, 71 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini's sharpest advantage is in agentic, where it averages 65.6 against 56.2. The single biggest benchmark swing on the page is HLE, 41.5% to 28.7%. Qwen3.5 397B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. GPT-5.4 mini is the reasoning model in the pair, while Qwen3.5 397B 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. GPT-5.4 mini gives you the larger context window at 400K, compared with 128K for Qwen3.5 397B.
GPT-5.4 mini is ahead on BenchLM's provisional leaderboard, 71 to 64. The biggest single separator in this matchup is HLE, where the scores are 41.5% and 28.7%.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 65.2 versus 57.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.4 mini has the edge for agentic tasks in this comparison, averaging 65.6 versus 56.2. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 76.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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