Model comparison
GLM-4.6 vs Ring-2.6-1T
GLM-4.6 has enough public results to be ranked (#135); Ring-2.6-1T does not yet, so treat this comparison as directional.
Last verified . 3 shared benchmarks.
Ant Group (inclusionAI)Summary
- They share 3 benchmarks with published results for both. GLM-4.6 scores higher in 0 categories and Ring-2.6-1T in 2 categories; one gap is clear of the uncertainty.
Side by side
| GLM-4.6 | Ring-2.6-1T | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Ant Group (inclusionAI) |
| Noometry Index | 41.4 | 36.9 |
| Released | 2025-09-30 | 2026-05-14 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 3 |
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Category by category
Coding Too close to call
GLM-4.6: 40.1 (#148), Ring-2.6-1T: 40.7
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| SciCode | 38.4% | 42.4% |
| ALE-Bench | 340.82 | 432.57 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| LMArena Coding | 1449 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.3 (#66), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning Ring-2.6-1T leads
GLM-4.6: 23.7 (#172), Ring-2.6-1T: 26.1
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| CritPt | 1.1% | 3.7% |
| Kagi LLM Benchmark | 47.4% | — |
| LMArena Hard Prompts | 1440 | — |
Math Not comparable
GLM-4.6: 39.1 (#111), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| LMArena Math | 1432 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
GLM-4.6: 40.2 (#124), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1431 | — |
Multilingual Not comparable
GLM-4.6: 53.5 (#66), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1499 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Russian | 1419 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
GLM-4.6: 74.3 (#98), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| LMArena Instruction Following | 1410 | — |
Long Context Not comparable
GLM-4.6: 43.4 (#94), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| LMArena Longer Query | 1422 | — |
Writing & Preference Not comparable
GLM-4.6: 61.1 (#90), Ring-2.6-1T: —
| Benchmark | GLM-4.6 | Ring-2.6-1T |
|---|---|---|
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| EQ-Bench Creative Writing | 1411 | — |
| LMArena Multi-Turn | 1427 | — |
Frequently asked questions
Is GLM-4.6 better than Ring-2.6-1T?
GLM-4.6 has enough public results to be ranked (#135); Ring-2.6-1T does not yet, so treat this comparison as directional.
Is GLM-4.6 or Ring-2.6-1T better for coding?
They score almost the same on coding (40.1 vs 40.7); test both on your own repository before choosing.
How many benchmarks do GLM-4.6 and Ring-2.6-1T share?
3 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Ring-2.6-1T has 3.