Model comparison
GLM-4.5 vs Olmo 2 0325 32b Instruct
GLM-4.5 is the stronger model overall, scoring 41.4 to 32.2 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-4.5 scores higher in 8 categories and Olmo 2 0325 32b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.5 leads 53.0 to 35.0.
Side by side
| GLM-4.5 | Olmo 2 0325 32b Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 41.4 | 32.2 |
| 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 | 16 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.1 (#121), Olmo 2 0325 32b Instruct: 34.6 (#222)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Coding | 1434 | 1210 |
| 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: 27.7 (#99), Olmo 2 0325 32b Instruct: 22.6 (#174)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1430 | 1208 |
| Kagi LLM Benchmark | 57.9% | — |
Math GLM-4.5 leads
GLM-4.5: 36.3 (#119), Olmo 2 0325 32b Instruct: 24.8 (#255)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Math | 1427 | 1208 |
| Omni-MATH | — | 16.1% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.5 (#172), Olmo 2 0325 32b Instruct: 19.2 (#274)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| Humanity's Last Exam | 8.3% | — |
| MMLU-Pro | — | 41.4% |
| Confabulations | 11.3% | — |
| GPQA (HELM) | — | 28.7% |
| LMArena Expert | 1433 | — |
Multilingual GLM-4.5 leads
GLM-4.5: 53.0 (#74), Olmo 2 0325 32b Instruct: 35.0 (#243)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Non-English | 1417 | 1160 |
| LMArena Chinese | 1465 | 1192 |
| LMArena Russian | 1414 | 1187 |
| LMArena French | 1423 | — |
| LMArena German | 1406 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1382 | — |
| LMArena Spanish | 1454 | — |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.3 (#100), Olmo 2 0325 32b Instruct: 61.8 (#238)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Instruction Following | 1405 | 1186 |
| IFEval | — | 78% |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#196), Olmo 2 0325 32b Instruct: 36.2 (#229)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Longer Query | 1413 | 1194 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.7 (#121), Olmo 2 0325 32b Instruct: 42.3 (#231)
| Benchmark | GLM-4.5 | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Text | 1430 | 1218 |
| LMArena Creative Writing | 1395 | 1199 |
| LMArena Multi-Turn | 1415 | 1221 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| WildBench | — | 73.4% |
Frequently asked questions
Is GLM-4.5 better than Olmo 2 0325 32b Instruct?
GLM-4.5 is the stronger model overall, scoring 41.4 to 32.2 on the Noometry Index.
Is GLM-4.5 or Olmo 2 0325 32b Instruct better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.1 versus 34.6 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Olmo 2 0325 32b Instruct share?
11 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Olmo 2 0325 32b Instruct has 16.