Model comparison
GLM-4.5V vs phi-3-medium 14B
GLM-4.5V is the stronger model overall, scoring 39.8 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
MicrosoftSummary
- The widest gap is in knowledge, where GLM-4.5V leads 37.5 to 9.1.
Side by side
| GLM-4.5V | phi-3-medium 14B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Microsoft |
| Noometry Index | 39.8 | 29.7 |
| Released | 2025-08-11 | 2024-04-23 |
| Weights | Open | Open |
| Context window | 64K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $1.80 | — |
| Results tracked | 15 | 13 |
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Category by category
Coding GLM-4.5V leads
GLM-4.5V: 39.5 (#155), phi-3-medium 14B: 36.8 (#201)
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1347 | — |
| BigCodeBench Complete | — | 48.7% |
Reasoning Not comparable
GLM-4.5V: 27.4 (#119), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | — |
| LMArena Hard Prompts | 1334 | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| Epoch Capabilities Index | — | 121.23 |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math GLM-4.5V leads
GLM-4.5V: 37.4 (#159), phi-3-medium 14B: 27.3 (#250)
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Math | 1354 | — |
| MATH Level 5 | — | 17.6% |
Knowledge GLM-4.5V leads
GLM-4.5V: 37.5 (#156), phi-3-medium 14B: 9.1 (#306)
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | — | 27.6% |
| LMArena Expert | 1353 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual Not comparable
GLM-4.5V: 44.6 (#177), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1303 | — |
| LMArena Chinese | 1337 | — |
| LMArena Russian | 1298 | — |
| LMArena Spanish | 1336 | — |
Instruction Following Not comparable
GLM-4.5V: 69.2 (#175), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1311 | — |
Long Context Not comparable
GLM-4.5V: 39.6 (#171), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Longer Query | 1304 | — |
Writing & Preference Not comparable
GLM-4.5V: 52.5 (#170), phi-3-medium 14B: —
| Benchmark | GLM-4.5V | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1333 | — |
| LMArena Creative Writing | 1295 | — |
| LMArena Multi-Turn | 1332 | — |
Frequently asked questions
Is GLM-4.5V better than phi-3-medium 14B?
GLM-4.5V is the stronger model overall, scoring 39.8 to 29.7 on the Noometry Index.
Is GLM-4.5V or phi-3-medium 14B better for coding?
GLM-4.5V scores higher on coding benchmarks: 39.5 versus 36.8 in the Noometry coding category.
How many benchmarks do GLM-4.5V and phi-3-medium 14B share?
0 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and phi-3-medium 14B has 13.