Model comparison
GLM-4.6V vs Olmo 3.1 32b Think
GLM-4.6V is the stronger model overall, scoring 41.3 to 37.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
Allen Institute for AI (Ai2)Summary
- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Olmo 3.1 32b Think in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6V leads 48.6 to 38.1.
Side by side
| GLM-4.6V | Olmo 3.1 32b Think | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 41.3 | 37.9 |
| Released | 2025-12-08 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 12 | 15 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.9 (#128), Olmo 3.1 32b Think: 37.7 (#189)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Coding | 1390 | 1291 |
Reasoning GLM-4.6V leads
GLM-4.6V: 27.6 (#115), Olmo 3.1 32b Think: 25.2 (#150)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1272 |
Math Not comparable
GLM-4.6V: —, Olmo 3.1 32b Think: 36.3 (#168)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Math | — | 1305 |
Knowledge GLM-4.6V leads
GLM-4.6V: 38.0 (#149), Olmo 3.1 32b Think: 35.7 (#181)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Expert | 1371 | 1295 |
Multimodal Not comparable
GLM-4.6V: 34.8 (#90), Olmo 3.1 32b Think: —
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual GLM-4.6V leads
GLM-4.6V: 48.6 (#141), Olmo 3.1 32b Think: 38.1 (#231)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Non-English | 1359 | 1209 |
| LMArena Chinese | 1425 | 1242 |
| LMArena Russian | 1340 | 1193 |
| LMArena French | — | 1260 |
| LMArena German | — | 1262 |
| LMArena Spanish | — | 1289 |
Instruction Following GLM-4.6V leads
GLM-4.6V: 71.4 (#151), Olmo 3.1 32b Think: 65.6 (#218)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Instruction Following | 1352 | 1247 |
Long Context GLM-4.6V leads
GLM-4.6V: 41.3 (#143), Olmo 3.1 32b Think: 38.6 (#195)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Longer Query | 1358 | 1272 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.6 (#137), Olmo 3.1 32b Think: 46.2 (#220)
| Benchmark | GLM-4.6V | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Text | 1377 | 1272 |
| LMArena Creative Writing | 1347 | 1226 |
| LMArena Multi-Turn | 1360 | 1252 |
Frequently asked questions
Is GLM-4.6V better than Olmo 3.1 32b Think?
GLM-4.6V is the stronger model overall, scoring 41.3 to 37.9 on the Noometry Index.
Is GLM-4.6V or Olmo 3.1 32b Think better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.9 versus 37.7 in the Noometry coding category.
How many benchmarks do GLM-4.6V and Olmo 3.1 32b Think share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Olmo 3.1 32b Think has 15.