Model comparison
GLM-5 vs Qwen-14B
GLM-5 is the stronger model overall, scoring 45.9 to 30.8 on the Noometry Index.
Last verified . 11 shared benchmarks.
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. GLM-5 scores higher in 7 categories and Qwen-14B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5 leads 66.2 to 27.8.
Side by side
| GLM-5 | Qwen-14B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 45.9 | 30.8 |
| Released | 2026-02-11 | 2023-09-24 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $3.20 | — |
| Results tracked | 45 | 18 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#47), Qwen-14B: 30.6 (#283)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Coding | 1461 | 1072 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 30.9 (#65), Qwen-14B: —
| Benchmark | GLM-5 | Qwen-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 GLM-5 leads
GLM-5: 27.6 (#100), Qwen-14B: 18.7 (#255)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1027 |
| Epoch Capabilities Index | 145.84 | 112.8 |
| 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% | — |
| BIG-Bench Hard | — | 55% |
| ForecastBench | 61 | — |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |
Math GLM-5 leads
GLM-5: 44.8 (#66), Qwen-14B: 28.7 (#224)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Math | 1440 | 1068 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 61.3% |
Knowledge Not comparable
GLM-5: 52.2 (#59), Qwen-14B: —
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |
Multilingual GLM-5 leads
GLM-5: 53.9 (#57), Qwen-14B: 27.7 (#270)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1430 | 1042 |
| LMArena Chinese | 1511 | 1077 |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1421 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1452 | — |
Instruction Following GLM-5 leads
GLM-5: 75.4 (#64), Qwen-14B: 52.6 (#284)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1427 | 1031 |
Long Context GLM-5 leads
GLM-5: 44.6 (#58), Qwen-14B: 31.3 (#276)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1446 | 1029 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.2 (#38), Qwen-14B: 27.8 (#294)
| Benchmark | GLM-5 | Qwen-14B |
|---|---|---|
| LMArena Text | 1446 | 1051 |
| LMArena Creative Writing | 1438 | 1028 |
| LMArena Multi-Turn | 1456 | 1022 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than Qwen-14B?
GLM-5 is the stronger model overall, scoring 45.9 to 30.8 on the Noometry Index.
Is GLM-5 or Qwen-14B better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 30.6 in the Noometry coding category.
How many benchmarks do GLM-5 and Qwen-14B share?
11 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen-14B has 18.