Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
74
Ornith-1.0-35B
67
Verified leaderboard positions: GLM-5.1 #30 · Ornith-1.0-35B unranked
Pick GLM-5.1 if you want the stronger benchmark profile. Ornith-1.0-35B only becomes the better choice if you want the cheaper token bill or you need the larger 262K context window.
Agentic
+1.1 difference
GLM-5.1
Ornith-1.0-35B
$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. Ornith-1.0-35B only becomes the better choice if you want the cheaper token bill or you need the larger 262K context window.
GLM-5.1 is clearly ahead on the provisional aggregate, 74 to 67. 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 64.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 64.2%.
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 Ornith-1.0-35B. That is roughly Infinityx on output cost alone. Ornith-1.0-35B 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 67. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 64.2%.
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.3 versus 64.2. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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