Model comparison
GLM-4.6 vs Llama 3.1-405B
GLM-4.6 is the stronger model overall, scoring 41.4 to 30.7 on the Noometry Index.
Last verified . 19 shared benchmarks.
MetaSummary
- They share 19 benchmarks with published results for both. GLM-4.6 scores higher in 9 categories and Llama 3.1-405B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 38.9.
Side by side
| GLM-4.6 | Llama 3.1-405B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 41.4 | 30.7 |
| Released | 2025-09-30 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-4.6 leads
GLM-4.6: 40.1 (#148), Llama 3.1-405B: 33.1 (#262)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Coding | 1449 | 1291 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| WeirdML | — | 21.4% |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use GLM-4.6 leads
GLM-4.6: 32.3 (#66), Llama 3.1-405B: 21.0 (#140)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |
Reasoning GLM-4.6 leads
GLM-4.6: 23.7 (#172), Llama 3.1-405B: 16.8 (#300)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 45% |
| LMArena Hard Prompts | 1440 | 1269 |
| SimpleBench | — | 23% |
| CritPt | 1.1% | — |
| DTBench | — | 61.4% |
| BIG-Bench Hard | — | 82.9% |
| Epoch Capabilities Index | — | 128.75 |
| ForecastBench | — | 59.9 |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |
Math GLM-4.6 leads
GLM-4.6: 39.1 (#111), Llama 3.1-405B: 18.4 (#290)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Math | 1432 | 1281 |
| OTIS Mock AIME 2024-2025 | — | 9.7% |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 40.2 (#124), Llama 3.1-405B: 30.4 (#227)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Expert | 1431 | 1243 |
| GPQA Diamond | — | 50.9% |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| Vectara Hallucination Rate | 9.5% | — |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |
Multilingual GLM-4.6 leads
GLM-4.6: 53.5 (#66), Llama 3.1-405B: 40.7 (#214)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1426 | 1248 |
| LMArena Chinese | 1499 | 1242 |
| LMArena French | 1459 | 1279 |
| LMArena German | 1447 | 1252 |
| LMArena Japanese | 1393 | 1208 |
| LMArena Korean | 1400 | 1184 |
| LMArena Russian | 1419 | 1265 |
| LMArena Spanish | 1436 | 1260 |
Instruction Following GLM-4.6 leads
GLM-4.6: 74.3 (#98), Llama 3.1-405B: 65.9 (#214)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1410 | 1259 |
| IFEval | — | 81.1% |
Long Context GLM-4.6 leads
GLM-4.6: 43.4 (#94), Llama 3.1-405B: 38.4 (#197)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1422 | 1266 |
Writing & Preference GLM-4.6 leads
GLM-4.6: 61.1 (#90), Llama 3.1-405B: 38.9 (#251)
| Benchmark | GLM-4.6 | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1440 | 1284 |
| LMArena Creative Writing | 1411 | 1262 |
| EQ-Bench Creative Writing | 1411 | 870 |
| LMArena Multi-Turn | 1427 | 1297 |
| WildBench | — | 78.3% |
Frequently asked questions
Is GLM-4.6 better than Llama 3.1-405B?
GLM-4.6 is the stronger model overall, scoring 41.4 to 30.7 on the Noometry Index.
Is GLM-4.6 or Llama 3.1-405B better for coding?
GLM-4.6 scores higher on coding benchmarks: 40.1 versus 33.1 in the Noometry coding category.
How many benchmarks do GLM-4.6 and Llama 3.1-405B share?
19 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Llama 3.1-405B has 42.