Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
83
Grok 4.3
79
Verified leaderboard positions: GLM-5.1 #21 · Grok 4.3 unranked
Pick GLM-5.1 if you want the stronger benchmark profile. Grok 4.3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+13.6 difference
Knowledge
+1.6 difference
GLM-5.1
Grok 4.3
$1.4 / $4.4
$1.25 / $2.5
N/A
209 t/s
N/A
12.36s
203K
1M
Pick GLM-5.1 if you want the stronger benchmark profile. Grok 4.3 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 79. 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 47.3. The single biggest benchmark swing on the page is HLE, 52.3% to 35%. Grok 4.3 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 $1.25 input / $2.50 output per 1M tokens for Grok 4.3. Grok 4.3 gives you the larger context window at 1M, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 83 to 79. The biggest single separator in this matchup is HLE, where the scores are 52.3% and 35%.
Grok 4.3 has the edge for knowledge tasks in this comparison, averaging 53.9 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 47.3. Grok 4.3 stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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