Model comparison
GLM-4.7 vs Qwen3.5-Flash
GLM-4.7 and Qwen3.5-Flash score almost the same on the Noometry Index (42.0 vs 42.5), so choose on price, context window or the category you care about most.
Last verified . 28 shared benchmarks.
Alibaba (Qwen)Summary
- They share 28 benchmarks with published results for both. GLM-4.7 scores higher in 7 categories and Qwen3.5-Flash in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7 leads 44.0 to 34.2.
- The biggest single-benchmark swing is Chess Puzzles: 6% for GLM-4.7 and 21% for Qwen3.5-Flash.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- Qwen3.5-Flash accepts more context: 1M tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7 | Qwen3.5-Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 42.5 |
| Released | 2025-12-22 | 2026-02-23 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.60 | $0.10 |
| Output $ / M tokens | $2.20 | $0.40 |
| Results tracked | 36 | 32 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| LMArena WebDev | 1435 | 1244 |
| LMArena Coding | 1454 | 1412 |
| ALE-Bench | 399.48 | 221.8 |
| SciCode | 45.1% | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.5 (#103), Qwen3.5-Flash: —
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | 2,377 | 462.69 |
| Terminal-Bench | 33.4% | — |
Reasoning Qwen3.5-Flash leads
GLM-4.7: 24.3 (#164), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| Chess Puzzles | 6% | 21% |
| LMArena Hard Prompts | 1443 | 1403 |
| Epoch Capabilities Index | 143.51 | 143.98 |
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LMCA | — | 29.1% |
Math GLM-4.7 leads
GLM-4.7: 38.6 (#135), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 84.4% |
| LMArena Math | 1423 | 1407 |
| FrontierMath (Feb 2025 set) | 2.4% | 6.2% |
| FrontierMath Tier 4 (v1) | 0% | 0% |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| ProofBench | 6% | — |
Knowledge GLM-4.7 leads
GLM-4.7: 47.0 (#80), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | 83.3% | 82.3% |
| SimpleQA Verified | 32.2% | 20.3% |
| Vectara Hallucination Rate | 11.7% | 10.5% |
| LMArena Expert | 1424 | 1407 |
Multilingual GLM-4.7 leads
GLM-4.7: 52.8 (#79), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1417 | 1385 |
| LMArena Chinese | 1495 | 1446 |
| LMArena French | 1432 | 1412 |
| LMArena German | 1424 | 1390 |
| LMArena Japanese | 1439 | 1368 |
| LMArena Korean | 1399 | 1344 |
| LMArena Russian | 1423 | 1379 |
| LMArena Spanish | 1434 | 1400 |
Instruction Following GLM-4.7 leads
GLM-4.7: 74.4 (#95), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1411 | 1374 |
Long Context Too close to call
GLM-4.7: 42.8 (#116), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1432 | 1392 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference GLM-4.7 leads
GLM-4.7: 60.9 (#93), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | GLM-4.7 | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1435 | 1397 |
| LMArena Creative Writing | 1401 | 1343 |
| LMArena Multi-Turn | 1446 | 1393 |
| EQ-Bench Creative Writing | 1413 | — |
Frequently asked questions
Is GLM-4.7 better than Qwen3.5-Flash?
GLM-4.7 and Qwen3.5-Flash score almost the same on the Noometry Index (42.0 vs 42.5), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.7 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-4.7 lists at $0.60 and $2.20.
Is GLM-4.7 or Qwen3.5-Flash better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 205K.
How many benchmarks do GLM-4.7 and Qwen3.5-Flash share?
28 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.5-Flash has 32.