Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
74
Qwen3.5-35B-A3B
55
Verified leaderboard positions: GLM-5.1 #30 · Qwen3.5-35B-A3B #27
Pick GLM-5.1 if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+14.7 difference
Coding
+2.5 difference
Knowledge
+27.0 difference
GLM-5.1
Qwen3.5-35B-A3B
$1.4 / $4.4
$0 / $0
N/A
N/A
N/A
N/A
203K
262K
Pick GLM-5.1 if you want the stronger benchmark profile. Qwen3.5-35B-A3B 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, 74 to 55. 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 agentic, where it averages 65.3 against 50.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 40.5%. Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B gives you the larger context window at 262K, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 74 to 55. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 40.5%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 52.3. Inside this category, AA-Omniscience Hallucination Rate 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 58.4. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.3 versus 50.6. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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