Model comparison
GLM-4.6 vs Llama 3.2 90B
GLM-4.6 is the stronger model overall, scoring 40.9 to 27.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
MetaSummary
- The widest gap is in math, where GLM-4.6 leads 36.4 to 10.4.
Side by side
| GLM-4.6 | Llama 3.2 90B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 40.9 | 27.1 |
| Released | 2025-09-30 | 2024-09-24 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 9 |
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Category by category
Coding Not comparable
GLM-4.6: 39.9 (#137), Llama 3.2 90B: —
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use GLM-4.6 leads
GLM-4.6: 32.1 (#60), Llama 3.2 90B: 29.7 (#73)
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
| BALROG | — | 27.3% |
Reasoning GLM-4.6 leads
GLM-4.6: 23.1 (#168), Llama 3.2 90B: 20.9 (#207)
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |
| EnigmaEval | — | 0.4% |
| LMArena Hard Prompts | 1440 | — |
| Epoch Capabilities Index | — | 125.5 |
Math GLM-4.6 leads
GLM-4.6: 36.4 (#115), Llama 3.2 90B: 10.4 (#302)
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.6% |
| LMArena Math | 1431 | — |
| MATH Level 5 | — | 39.4% |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 39.6 (#118), Llama 3.2 90B: 21.7 (#269)
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| GPQA Diamond | — | 41% |
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1432 | — |
| MMLU | — | 80.3% |
Multimodal Not comparable
GLM-4.6: —, Llama 3.2 90B: 24.9 (#119)
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| LMArena Vision | — | 1000 |
| GeoBench | — | 52% |
Multilingual Not comparable
GLM-4.6: 53.6 (#62), Llama 3.2 90B: —
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1500 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1418 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
GLM-4.6: 74.5 (#93), Llama 3.2 90B: —
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| LMArena Instruction Following | 1410 | — |
Long Context Not comparable
GLM-4.6: 43.4 (#91), Llama 3.2 90B: —
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| LMArena Longer Query | 1423 | — |
Writing & Preference Not comparable
GLM-4.6: 61.3 (#86), Llama 3.2 90B: —
| Benchmark | GLM-4.6 | Llama 3.2 90B |
|---|---|---|
| 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 Llama 3.2 90B?
GLM-4.6 is the stronger model overall, scoring 40.9 to 27.1 on the Noometry Index.
How many benchmarks do GLM-4.6 and Llama 3.2 90B share?
0 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Llama 3.2 90B has 9.