Model comparison
GLM-4.5 vs phi-3-medium 14B
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
MicrosoftSummary
- The widest gap is in knowledge, where GLM-4.5 leads 35.9 to 9.1.
Side by side
| GLM-4.5 | phi-3-medium 14B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Microsoft |
| Noometry Index | 42.0 | 29.7 |
| Released | 2025-07-27 | 2024-04-23 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 13 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), phi-3-medium 14B: 36.8 (#201)
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1434 | — |
| BigCodeBench Complete | — | 48.7% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning Not comparable
GLM-4.5: 28.6 (#100), phi-3-medium 14B: —
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | — |
| LMArena Hard Prompts | 1429 | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| Epoch Capabilities Index | — | 121.23 |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), phi-3-medium 14B: 27.3 (#250)
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| LMArena Math | 1427 | — |
| MATH Level 5 | — | 17.6% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), phi-3-medium 14B: 9.1 (#306)
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | — | 27.6% |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| LMArena Expert | 1433 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multilingual Not comparable
GLM-4.5: 52.8 (#77), phi-3-medium 14B: —
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1465 | — |
| LMArena French | 1418 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1414 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-4.5: 74.1 (#104), phi-3-medium 14B: —
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
GLM-4.5: 38.2 (#201), phi-3-medium 14B: —
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| Fiction.LiveBench | 58.3% | — |
| LMArena Longer Query | 1412 | — |
Writing & Preference Not comparable
GLM-4.5: 57.5 (#127), phi-3-medium 14B: —
| Benchmark | GLM-4.5 | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1430 | — |
| LMArena Creative Writing | 1395 | — |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| LMArena Multi-Turn | 1415 | — |
Frequently asked questions
Is GLM-4.5 better than phi-3-medium 14B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.7 on the Noometry Index.
Is GLM-4.5 or phi-3-medium 14B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 36.8 in the Noometry coding category.
How many benchmarks do GLM-4.5 and phi-3-medium 14B share?
0 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and phi-3-medium 14B has 13.