Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
65
GPT-5.4
89
Verified leaderboard positions: Gemma 4 31B unranked · GPT-5.4 #14
Pick GPT-5.4 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Coding
+16.1 difference
Knowledge
+4.8 difference
Multimodal
+4.2 difference
Gemma 4 31B
GPT-5.4
$0 / $0
$2.5 / $15
N/A
74 t/s
N/A
151.79s
256K
1.05M
Pick GPT-5.4 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
GPT-5.4 is clearly ahead on the provisional aggregate, 89 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4's sharpest advantage is in coding, where it averages 57.7 against 41.6. The single biggest benchmark swing on the page is HLE, 26.5% to 52.1%. Gemma 4 31B does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 31B. That is roughly Infinityx on output cost alone. GPT-5.4 gives you the larger context window at 1.05M, compared with 256K for Gemma 4 31B.
GPT-5.4 is ahead on BenchLM's provisional leaderboard, 89 to 65. The biggest single separator in this matchup is HLE, where the scores are 26.5% and 52.1%.
GPT-5.4 has the edge for knowledge tasks in this comparison, averaging 66.1 versus 61.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for coding in this comparison, averaging 57.7 versus 41.6. Inside this category, React Native Evals is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 72.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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