Model comparison
GLM-4.7-Flash vs Qwen3.5-9B
GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 33.3 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GLM-4.7-Flash scores higher in 2 categories and Qwen3.5-9B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 35.4.
- The biggest single-benchmark swing is GPQA Diamond: 60.5% for GLM-4.7-Flash and 79% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
- Qwen3.5-9B accepts more context: 262K tokens versus 200K.
Side by side
| GLM-4.7-Flash | Qwen3.5-9B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.4 | 33.3 |
| Released | 2026-01-19 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 200K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.06 | $0.10 |
| Output $ / M tokens | $0.40 | $0.15 |
| Results tracked | 21 | 10 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.0 (#133), Qwen3.5-9B: 35.3 (#213)
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| SciCode | — | 27.5% |
| LMArena Coding | 1383 | — |
Agentic & Tool Use Not comparable
GLM-4.7-Flash: —, Qwen3.5-9B: 14.4 (#143)
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |
Reasoning Qwen3.5-9B leads
GLM-4.7-Flash: 20.2 (#224), Qwen3.5-9B: 22.5 (#178)
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| Chess Puzzles | 0% | 12% |
| CritPt | — | 0.3% |
| LMArena Hard Prompts | 1356 | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
| Epoch Capabilities Index | — | 139.45 |
Math Too close to call
GLM-4.7-Flash: 34.4 (#159), Qwen3.5-9B: 33.5 (#174)
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 61.7% |
| MathArena Final-Answer Competitions | — | 48.5% |
| LMArena Math | 1354 | — |
Knowledge Qwen3.5-9B leads
GLM-4.7-Flash: 35.4 (#177), Qwen3.5-9B: 46.0 (#77)
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | 60.5% | 79% |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |
Multilingual Not comparable
GLM-4.7-Flash: 46.8 (#152), Qwen3.5-9B: —
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1331 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1336 | — |
| LMArena Korean | 1284 | — |
| LMArena Russian | 1333 | — |
| LMArena Spanish | 1351 | — |
Instruction Following Not comparable
GLM-4.7-Flash: 70.3 (#162), Qwen3.5-9B: —
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1327 | — |
Long Context Not comparable
GLM-4.7-Flash: 40.9 (#143), Qwen3.5-9B: —
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| LMArena Longer Query | 1345 | — |
Writing & Preference Not comparable
GLM-4.7-Flash: 47.7 (#206), Qwen3.5-9B: —
| Benchmark | GLM-4.7-Flash | Qwen3.5-9B |
|---|---|---|
| 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 Qwen3.5-9B?
GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 33.3 on the Noometry Index.
Which is cheaper, GLM-4.7-Flash or Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.
Is GLM-4.7-Flash or Qwen3.5-9B better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.0 versus 35.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-9B does, with 262K tokens against 200K.
How many benchmarks do GLM-4.7-Flash and Qwen3.5-9B share?
3 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen3.5-9B has 10.