Model comparison
GLM-5 vs phi-3-medium 14B
GLM-5 is the stronger model overall, scoring 46.1 to 29.7 on the Noometry Index.
Last verified . 2 shared benchmarks.
MicrosoftSummary
- They share 2 benchmarks with published results for both. GLM-5 scores higher in 3 categories and phi-3-medium 14B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 9.1.
- The biggest single-benchmark swing is GPQA Diamond: 87.8% for GLM-5 and 27.6% for phi-3-medium 14B.
Side by side
| GLM-5 | phi-3-medium 14B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Microsoft |
| Noometry Index | 46.1 | 29.7 |
| Released | 2026-02-11 | 2024-04-23 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $3.20 | — |
| Results tracked | 45 | 13 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), phi-3-medium 14B: 36.8 (#201)
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1461 | — |
| BigCodeBench Complete | — | 48.7% |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning Not comparable
GLM-5: 27.6 (#116), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| Epoch Capabilities Index | 145.83 | 121.23 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| LMArena Hard Prompts | 1452 | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| ForecastBench | 61 | — |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math GLM-5 leads
GLM-5: 46.4 (#71), phi-3-medium 14B: 27.3 (#250)
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| LMArena Math | 1440 | — |
| MATH Level 5 | — | 17.6% |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), phi-3-medium 14B: 9.1 (#306)
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | 87.8% | 27.6% |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multilingual Not comparable
GLM-5: 53.7 (#58), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1423 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-5: 75.2 (#67), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1428 | — |
Long Context Not comparable
GLM-5: 44.7 (#60), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |
Writing & Preference Not comparable
GLM-5: 66.0 (#38), phi-3-medium 14B: —
| Benchmark | GLM-5 | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1439 | — |
| EQ-Bench Creative Writing | 1601 | — |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is GLM-5 better than phi-3-medium 14B?
GLM-5 is the stronger model overall, scoring 46.1 to 29.7 on the Noometry Index.
Is GLM-5 or phi-3-medium 14B better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 36.8 in the Noometry coding category.
How many benchmarks do GLM-5 and phi-3-medium 14B share?
2 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and phi-3-medium 14B has 13.