Model comparison
GLM-4.6V vs Qwen3.5-9B
GLM-4.6V is the stronger model overall, scoring 40.9 to 33.3 on the Noometry Index. Qwen3.5-9B costs 4.0× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 37.4.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
- Qwen3.5-9B accepts more context: 262K tokens versus 128K.
Side by side
| GLM-4.6V | Qwen3.5-9B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 40.9 | 33.3 |
| Released | 2025-12-08 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 33K | 66K |
| Input $ / M tokens | $0.30 | $0.10 |
| Output $ / M tokens | $0.90 | $0.15 |
| Results tracked | 12 | 10 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.2 (#128), Qwen3.5-9B: 35.3 (#213)
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| SciCode | — | 27.5% |
| LMArena Coding | 1390 | — |
Agentic & Tool Use Not comparable
GLM-4.6V: —, Qwen3.5-9B: 14.4 (#143)
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |
Reasoning GLM-4.6V leads
GLM-4.6V: 26.5 (#117), Qwen3.5-9B: 22.5 (#178)
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |
| LMArena Hard Prompts | 1368 | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
| Epoch Capabilities Index | — | 139.45 |
Math Not comparable
GLM-4.6V: —, Qwen3.5-9B: 33.5 (#174)
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |
Knowledge Qwen3.5-9B leads
GLM-4.6V: 37.4 (#148), Qwen3.5-9B: 46.0 (#77)
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| LMArena Expert | 1372 | — |
Multimodal Not comparable
GLM-4.6V: 34.2 (#83), Qwen3.5-9B: —
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual Not comparable
GLM-4.6V: 48.8 (#135), Qwen3.5-9B: —
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1359 | — |
| LMArena Chinese | 1426 | — |
| LMArena Russian | 1341 | — |
Instruction Following Not comparable
GLM-4.6V: 71.6 (#145), Qwen3.5-9B: —
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1351 | — |
Long Context Not comparable
GLM-4.6V: 41.3 (#138), Qwen3.5-9B: —
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Longer Query | 1358 | — |
Writing & Preference Not comparable
GLM-4.6V: 56.8 (#132), Qwen3.5-9B: —
| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1377 | — |
| LMArena Creative Writing | 1347 | — |
| LMArena Multi-Turn | 1359 | — |
Frequently asked questions
Is GLM-4.6V better than Qwen3.5-9B?
GLM-4.6V is the stronger model overall, scoring 40.9 to 33.3 on the Noometry Index. Qwen3.5-9B costs 4.0× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.
Which is cheaper, GLM-4.6V 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-4.6V lists at $0.30 and $0.90.
Is GLM-4.6V or Qwen3.5-9B better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.2 versus 35.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-9B does, with 262K tokens against 128K.
How many benchmarks do GLM-4.6V and Qwen3.5-9B share?
0 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3.5-9B has 10.