Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
82
Ling 2.6 Flash
36
Verified leaderboard positions: GLM-5.1 #25 · Ling 2.6 Flash unranked
Pick GLM-5.1 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Coding
+33.9 difference
Knowledge
+6.7 difference
GLM-5.1
Ling 2.6 Flash
$1.4 / $4.4
$null / $null
N/A
209.5 t/s
N/A
1.07s
203K
262K
Pick GLM-5.1 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
GLM-5.1 is clearly ahead on the provisional aggregate, 82 to 36. 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 27. Ling 2.6 Flash 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 the reasoning model in the pair, while Ling 2.6 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Ling 2.6 Flash 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, 82 to 36.
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 52.3. Inside this category, AA-Omniscience Index 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 27. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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