Model comparison
GLM-4.7-Flash vs Qwen3 8B
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 33.7 on the Noometry Index.
Last verified . 4 shared benchmarks.
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. GLM-4.7-Flash scores higher in 4 categories and Qwen3 8B in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7-Flash leads 40.6 to 34.0.
- The biggest single-benchmark swing is Chess Puzzles: 0% for GLM-4.7-Flash and 5% for Qwen3 8B.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.18 / $0.70 for Qwen3 8B.
- GLM-4.7-Flash accepts more context: 200K tokens versus 131K.
Side by side
| GLM-4.7-Flash | Qwen3 8B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.8 | 33.7 |
| Released | 2026-01-19 | 2025-04 |
| Weights | Open | Open |
| Context window | 200K | 131K |
| Max output | 131K | 8K |
| Input $ / M tokens | $0.06 | $0.18 |
| Output $ / M tokens | $0.40 | $0.70 |
| Results tracked | 21 | 11 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Qwen3 8B: 34.0 (#248)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| SciCode | — | 22.6% |
| LMArena Coding | 1383 | — |
Agentic & Tool Use Not comparable
GLM-4.7-Flash: —, Qwen3 8B: 30.2 (#78)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 42.6% |
Reasoning GLM-4.7-Flash leads
GLM-4.7-Flash: 20.9 (#229), Qwen3 8B: 16.6 (#303)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| Chess Puzzles | 0% | 5% |
| CritPt | — | 0% |
| LMArena Hard Prompts | 1356 | — |
| DTBench | — | 59.7% |
| LMCA | — | 8.8% |
| Epoch Capabilities Index | — | 136.17 |
Math GLM-4.7-Flash leads
GLM-4.7-Flash: 36.1 (#173), Qwen3 8B: 34.9 (#191)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 56.1% |
| LMArena Math | 1355 | — |
Knowledge Too close to call
GLM-4.7-Flash: 35.5 (#184), Qwen3 8B: 36.1 (#173)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| GPQA Diamond | 60.5% | 56.8% |
| Vectara Hallucination Rate | 9.3% | 4.8% |
| LMArena Expert | 1357 | — |
Multilingual Not comparable
GLM-4.7-Flash: 46.5 (#158), Qwen3 8B: —
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| LMArena Non-English | 1330 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |
Instruction Following Not comparable
GLM-4.7-Flash: 70.1 (#167), Qwen3 8B: —
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| LMArena Instruction Following | 1327 | — |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Qwen3 8B: 37.9 (#210)
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| Fiction.LiveBench | — | 62.1% |
| LMArena Longer Query | 1345 | — |
Writing & Preference Not comparable
GLM-4.7-Flash: 47.4 (#210), Qwen3 8B: —
| Benchmark | GLM-4.7-Flash | Qwen3 8B |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1297 | — |
| EQ-Bench Creative Writing | 1125 | — |
| LMArena Multi-Turn | 1342 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Qwen3 8B?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 33.7 on the Noometry Index.
Which is cheaper, GLM-4.7-Flash or Qwen3 8B?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Qwen3 8B lists at $0.18 and $0.70.
Is GLM-4.7-Flash or Qwen3 8B better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 131K.
How many benchmarks do GLM-4.7-Flash and Qwen3 8B share?
4 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen3 8B has 11.