Model comparison
GLM-4.6 vs Longcat Flash Chat
GLM-4.6 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 . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-4.6 scores higher in 3 categories and Longcat Flash Chat in 5 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6 leads 23.1 to 18.3.
Side by side
| GLM-4.6 | Longcat Flash Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meituan |
| Noometry Index | 40.9 | 41.5 |
| Released | 2025-09-30 | — |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 19 |
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Category by category
Coding Longcat Flash Chat leads
GLM-4.6: 39.9 (#137), Longcat Flash Chat: 42.9 (#85)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Coding | 1449 | 1471 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.1 (#60), Longcat Flash Chat: —
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning GLM-4.6 leads
GLM-4.6: 23.1 (#168), Longcat Flash Chat: 18.3 (#267)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 43.9% |
| LMArena Hard Prompts | 1440 | 1440 |
| NYT Connections (extended) | — | 17.7% |
| CritPt | 1.1% | — |
Math Too close to call
GLM-4.6: 36.4 (#115), Longcat Flash Chat: 36.6 (#107)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Math | 1431 | 1441 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Too close to call
GLM-4.6: 39.6 (#118), Longcat Flash Chat: 40.0 (#111)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Expert | 1432 | 1454 |
| Vectara Hallucination Rate | 9.5% | — |
Multilingual GLM-4.6 leads
GLM-4.6: 53.6 (#62), Longcat Flash Chat: 52.1 (#95)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Non-English | 1426 | 1404 |
| LMArena Chinese | 1500 | 1465 |
| LMArena French | 1459 | 1457 |
| LMArena German | 1447 | 1409 |
| LMArena Japanese | 1394 | 1373 |
| LMArena Korean | 1401 | 1372 |
| LMArena Russian | 1418 | 1396 |
| LMArena Spanish | 1436 | 1445 |
Instruction Following Too close to call
GLM-4.6: 74.5 (#93), Longcat Flash Chat: 74.6 (#92)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Instruction Following | 1410 | 1411 |
Long Context Too close to call
GLM-4.6: 43.4 (#91), Longcat Flash Chat: 43.5 (#89)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Longer Query | 1423 | 1425 |
Writing & Preference Too close to call
GLM-4.6: 61.3 (#86), Longcat Flash Chat: 61.2 (#88)
| Benchmark | GLM-4.6 | Longcat Flash Chat |
|---|---|---|
| LMArena Text | 1440 | 1427 |
| LMArena Creative Writing | 1411 | 1388 |
| LMArena Multi-Turn | 1427 | 1418 |
| EQ-Bench Creative Writing | 1411 | — |
Frequently asked questions
Is GLM-4.6 better than Longcat Flash Chat?
GLM-4.6 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-4.6 or Longcat Flash Chat better for coding?
Longcat Flash Chat scores higher on coding benchmarks: 42.9 versus 39.9 in the Noometry coding category.
How many benchmarks do GLM-4.6 and Longcat Flash Chat share?
18 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Longcat Flash Chat has 19.