Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
62
GPT-5.2
79
Pick GPT-5.2 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you want the cheaper token bill.
Coding
+23.1 difference
Knowledge
+31.1 difference
Multimodal
+3.4 difference
Gemma 4 31B
GPT-5.2
$0 / $0
$1.75 / $14
N/A
73 t/s
N/A
130.34s
256K
400K
Pick GPT-5.2 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you want the cheaper token bill.
GPT-5.2 is clearly ahead on the provisional aggregate, 79 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 61.3. The single biggest benchmark swing on the page is GPQA, 84.3% to 92.4%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 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-5.2 gives you the larger context window at 400K, compared with 256K for Gemma 4 31B.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 62. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 92.4%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 61.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 64.7 versus 41.6. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.3 versus 76.9. 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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