Model comparison
GLM-4.5V vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 39.2 on the Noometry Index. GLM-4.5V costs 1.5× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 36.8.
- GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B accepts more context: 262K tokens versus 64K.
Side by side
| GLM-4.5V | Qwen3.6 27B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 39.2 | 41.9 |
| Released | 2025-08-11 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 64K | 262K |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.60 | $0.60 |
| Output $ / M tokens | $1.80 | $3.60 |
| Results tracked | 15 | 11 |
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Category by category
Coding Too close to call
GLM-4.5V: 38.9 (#152), Qwen3.6 27B: 38.5 (#162)
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
| LMArena Coding | 1347 | — |
Reasoning GLM-4.5V leads
GLM-4.5V: 26.5 (#118), Qwen3.6 27B: 24.4 (#148)
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | — |
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| LMArena Hard Prompts | 1335 | — |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
| Epoch Capabilities Index | — | 146.47 |
Math Qwen3.6 27B leads
GLM-4.5V: 34.7 (#157), Qwen3.6 27B: 47.5 (#56)
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| LMArena Math | 1353 | — |
Knowledge Qwen3.6 27B leads
GLM-4.5V: 36.8 (#155), Qwen3.6 27B: 52.4 (#58)
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
| LMArena Expert | 1353 | — |
Multimodal Not comparable
GLM-4.5V: 33.6 (#86), Qwen3.6 27B: —
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual Not comparable
GLM-4.5V: 44.9 (#172), Qwen3.6 27B: —
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| LMArena Non-English | 1304 | — |
| LMArena Chinese | 1338 | — |
| LMArena Russian | 1299 | — |
| LMArena Spanish | 1335 | — |
Instruction Following Not comparable
GLM-4.5V: 69.4 (#170), Qwen3.6 27B: —
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| LMArena Instruction Following | 1311 | — |
Long Context Not comparable
GLM-4.5V: 39.6 (#166), Qwen3.6 27B: —
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1305 | — |
Writing & Preference GLM-4.5V leads
GLM-4.5V: 52.7 (#162), Qwen3.6 27B: 50.3 (#180)
| Benchmark | GLM-4.5V | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1333 | — |
| LMArena Creative Writing | 1295 | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1333 | — |
Frequently asked questions
Is GLM-4.5V better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 39.2 on the Noometry Index. GLM-4.5V costs 1.5× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5V or Qwen3.6 27B?
GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Is GLM-4.5V or Qwen3.6 27B better for coding?
They score almost the same on coding (38.9 vs 38.5); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 64K.
How many benchmarks do GLM-4.5V and Qwen3.6 27B share?
0 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Qwen3.6 27B has 11.