Model comparison
GLM-5V-Turbo vs Qwen3.5-Flash
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 42.5 on the Noometry Index. Qwen3.5-Flash costs 11× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. GLM-5V-Turbo scores higher in 6 categories and Qwen3.5-Flash in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5V-Turbo leads 42.1 to 34.2.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- Qwen3.5-Flash accepts more context: 1M tokens versus 200K.
Side by side
| GLM-5V-Turbo | Qwen3.5-Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 43.8 | 42.5 |
| Released | 2026-04-01 | 2026-02-23 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1M |
| Max output | 131K | 66K |
| Input $ / M tokens | $1.20 | $0.10 |
| Output $ / M tokens | $4 | $0.40 |
| Results tracked | 19 | 32 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 42.1 (#111), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena WebDev | 1401 | 1244 |
| LMArena Coding | 1466 | 1412 |
| ALE-Bench | — | 221.8 |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, Qwen3.5-Flash: —
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
GLM-5V-Turbo: 29.7 (#89), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1403 |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LMCA | — | 29.1% |
| Epoch Capabilities Index | — | 143.98 |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 39.4 (#106), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Math | 1441 | 1407 |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3.5-Flash leads
GLM-5V-Turbo: 40.6 (#117), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Expert | 1452 | 1407 |
| GPQA Diamond | — | 82.3% |
| SimpleQA Verified | — | 20.3% |
| Vectara Hallucination Rate | — | 10.5% |
Multimodal Not comparable
GLM-5V-Turbo: 40.9 (#42), Qwen3.5-Flash: —
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Vision | 1264 | — |
| LMArena Document | 1416 | — |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.0 (#73), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1420 | 1385 |
| LMArena Chinese | 1488 | 1446 |
| LMArena French | 1444 | 1412 |
| LMArena German | 1423 | 1390 |
| LMArena Korean | 1396 | 1344 |
| LMArena Russian | 1431 | 1379 |
| LMArena Spanish | 1450 | 1400 |
| LMArena Japanese | — | 1368 |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.0 (#80), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1423 | 1374 |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#80), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1438 | 1392 |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | GLM-5V-Turbo | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1437 | 1397 |
| LMArena Creative Writing | 1416 | 1343 |
| LMArena Multi-Turn | 1432 | 1393 |
Frequently asked questions
Is GLM-5V-Turbo better than Qwen3.5-Flash?
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 42.5 on the Noometry Index. Qwen3.5-Flash costs 11× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Which is cheaper, GLM-5V-Turbo or Qwen3.5-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5V-Turbo or Qwen3.5-Flash better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 200K.
How many benchmarks do GLM-5V-Turbo and Qwen3.5-Flash share?
17 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Qwen3.5-Flash has 32.