Model comparison
GLM-4.5 vs Olmo 3.1 32b Think
GLM-4.5 is the stronger model overall, scoring 42.0 to 37.9 on the Noometry Index.
Last verified . 15 shared benchmarks.
Allen Institute for AI (Ai2)Summary
- They share 15 benchmarks with published results for both. GLM-4.5 scores higher in 7 categories and Olmo 3.1 32b Think in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.5 leads 52.8 to 38.1.
Side by side
| GLM-4.5 | Olmo 3.1 32b Think | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 42.0 | 37.9 |
| Released | 2025-07-27 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 15 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Olmo 3.1 32b Think: 37.7 (#189)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Coding | 1434 | 1291 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Olmo 3.1 32b Think: 25.2 (#150)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1272 |
| Kagi LLM Benchmark | 57.9% | — |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Olmo 3.1 32b Think: 36.3 (#168)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Math | 1427 | 1305 |
Knowledge Too close to call
GLM-4.5: 35.9 (#179), Olmo 3.1 32b Think: 35.7 (#181)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Expert | 1433 | 1295 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Olmo 3.1 32b Think: 38.1 (#231)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Non-English | 1417 | 1209 |
| LMArena Chinese | 1465 | 1242 |
| LMArena French | 1418 | 1260 |
| LMArena German | 1407 | 1262 |
| LMArena Russian | 1414 | 1193 |
| LMArena Spanish | 1454 | 1289 |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Olmo 3.1 32b Think: 65.6 (#218)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Instruction Following | 1404 | 1247 |
Long Context Too close to call
GLM-4.5: 38.2 (#201), Olmo 3.1 32b Think: 38.6 (#195)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Longer Query | 1412 | 1272 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Olmo 3.1 32b Think: 46.2 (#220)
| Benchmark | GLM-4.5 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Text | 1430 | 1272 |
| LMArena Creative Writing | 1395 | 1226 |
| LMArena Multi-Turn | 1415 | 1252 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Olmo 3.1 32b Think?
GLM-4.5 is the stronger model overall, scoring 42.0 to 37.9 on the Noometry Index.
Is GLM-4.5 or Olmo 3.1 32b Think better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 37.7 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Olmo 3.1 32b Think share?
15 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Olmo 3.1 32b Think has 15.