Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
65
GLM-5.1
83
Verified leaderboard positions: Gemma 4 31B unranked · GLM-5.1 #23
Pick GLM-5.1 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+19.3 difference
Knowledge
+9.0 difference
Gemma 4 31B
GLM-5.1
$0 / $0
$1.4 / $4.4
N/A
N/A
N/A
N/A
256K
203K
Pick GLM-5.1 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GLM-5.1 is clearly ahead on the provisional aggregate, 83 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in coding, where it averages 60.9 against 41.6. The single biggest benchmark swing on the page is HLE, 26.5% to 52.3%. Gemma 4 31B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GLM-5.1 is also the more expensive model on tokens at $1.40 input / $4.40 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. Gemma 4 31B gives you the larger context window at 256K, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 65. The biggest single separator in this matchup is HLE, where the scores are 26.5% and 52.3%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 52.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
GLM-5.1 has the edge for coding in this comparison, averaging 60.9 versus 41.6. Inside this category, SWE-Rebench is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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