Model comparison
GLM-4.6V vs Longcat Flash Chat
GLM-4.6V and Longcat Flash Chat score almost the same on the Noometry Index (40.9 vs 41.5), so choose on price, context window or the category you care about most.
Last verified . 11 shared benchmarks.
Summary
- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 1 category and Longcat Flash Chat in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 18.3.
Side by side
| GLM-4.6V | Longcat Flash Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meituan |
| Noometry Index | 40.9 | 41.5 |
| Released | 2025-12-08 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 12 | 19 |
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Category by category
Coding Longcat Flash Chat leads
GLM-4.6V: 40.2 (#128), Longcat Flash Chat: 42.9 (#85)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Coding | 1390 | 1471 |
Reasoning GLM-4.6V leads
GLM-4.6V: 26.5 (#117), Longcat Flash Chat: 18.3 (#267)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1440 |
| Kagi LLM Benchmark | — | 43.9% |
| NYT Connections (extended) | — | 17.7% |
Math Not comparable
GLM-4.6V: —, Longcat Flash Chat: 36.6 (#107)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Math | — | 1441 |
Knowledge Longcat Flash Chat leads
GLM-4.6V: 37.4 (#148), Longcat Flash Chat: 40.0 (#111)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Expert | 1372 | 1454 |
Multimodal Not comparable
GLM-4.6V: 34.2 (#83), Longcat Flash Chat: —
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual Longcat Flash Chat leads
GLM-4.6V: 48.8 (#135), Longcat Flash Chat: 52.1 (#95)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Non-English | 1359 | 1404 |
| LMArena Chinese | 1426 | 1465 |
| LMArena Russian | 1341 | 1396 |
| LMArena French | — | 1457 |
| LMArena German | — | 1409 |
| LMArena Japanese | — | 1373 |
| LMArena Korean | — | 1372 |
| LMArena Spanish | — | 1445 |
Instruction Following Longcat Flash Chat leads
GLM-4.6V: 71.6 (#145), Longcat Flash Chat: 74.6 (#92)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Instruction Following | 1351 | 1411 |
Long Context Longcat Flash Chat leads
GLM-4.6V: 41.3 (#138), Longcat Flash Chat: 43.5 (#89)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Longer Query | 1358 | 1425 |
Writing & Preference Longcat Flash Chat leads
GLM-4.6V: 56.8 (#132), Longcat Flash Chat: 61.2 (#88)
| Benchmark | GLM-4.6V | Longcat Flash Chat |
|---|---|---|
| LMArena Text | 1377 | 1427 |
| LMArena Creative Writing | 1347 | 1388 |
| LMArena Multi-Turn | 1359 | 1418 |
Frequently asked questions
Is GLM-4.6V better than Longcat Flash Chat?
GLM-4.6V and Longcat Flash Chat score almost the same on the Noometry Index (40.9 vs 41.5), so choose on price, context window or the category you care about most.
Is GLM-4.6V or Longcat Flash Chat better for coding?
Longcat Flash Chat scores higher on coding benchmarks: 42.9 versus 40.2 in the Noometry coding category.
How many benchmarks do GLM-4.6V and Longcat Flash Chat share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Longcat Flash Chat has 19.