Model comparison
GLM-4.7-Flash vs Qwen-14B
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.4 on the Noometry Index.
Last verified . 10 shared benchmarks.
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. GLM-4.7-Flash 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-4.7-Flash leads 47.4 to 27.6.
Side by side
| GLM-4.7-Flash | Qwen-14B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.8 | 31.4 |
| Released | 2026-01-19 | 2023-09-24 |
| Weights | Open | Open |
| Context window | 200K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.06 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 21 | 18 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Qwen-14B: 31.2 (#288)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Coding | 1383 | 1071 |
Reasoning GLM-4.7-Flash leads
GLM-4.7-Flash: 20.9 (#229), Qwen-14B: 19.6 (#257)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1027 |
| Chess Puzzles | 0% | — |
| BIG-Bench Hard | — | 55% |
| Epoch Capabilities Index | — | 113.03 |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |
Math GLM-4.7-Flash leads
GLM-4.7-Flash: 36.1 (#173), Qwen-14B: 31.2 (#227)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Math | 1355 | 1068 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| GSM8K | — | 61.3% |
Knowledge Not comparable
GLM-4.7-Flash: 35.5 (#184), Qwen-14B: —
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Qwen-14B: 27.5 (#275)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1330 | 1041 |
| LMArena Chinese | 1403 | 1077 |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Qwen-14B: 52.4 (#289)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1327 | 1031 |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Qwen-14B: 31.3 (#280)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1345 | 1028 |
Writing & Preference GLM-4.7-Flash leads
GLM-4.7-Flash: 47.4 (#210), Qwen-14B: 27.6 (#299)
| Benchmark | GLM-4.7-Flash | Qwen-14B |
|---|---|---|
| LMArena Text | 1351 | 1051 |
| LMArena Creative Writing | 1297 | 1028 |
| LMArena Multi-Turn | 1342 | 1022 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Qwen-14B?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.4 on the Noometry Index.
Is GLM-4.7-Flash or Qwen-14B better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 31.2 in the Noometry coding category.
How many benchmarks do GLM-4.7-Flash and Qwen-14B share?
10 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen-14B has 18.