Model comparison
GLM-4.5-Air vs Llama 2-13B
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 29.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. GLM-4.5-Air scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5-Air leads 55.9 to 29.8.
Side by side
| GLM-4.5-Air | Llama 2-13B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 38.9 | 29.6 |
| Released | 2025-07-20 | 2023-07-18 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.20 | — |
| Output $ / M tokens | $1.10 | — |
| Results tracked | 27 | 32 |
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Category by category
Coding GLM-4.5-Air leads
GLM-4.5-Air: 33.3 (#259), Llama 2-13B: 30.9 (#291)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1397 | 1062 |
| GSO | 2.9% | — |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), Llama 2-13B: 12.8 (#337)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1051 |
| Kagi LLM Benchmark | 43% | — |
| Chess Puzzles | — | 0% |
| DTBench | — | 42.2% |
| BIG-Bench Hard | — | 58.2% |
| Epoch Capabilities Index | — | 106.17 |
| ForecastBench | 59.2 | — |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |
Math GLM-4.5-Air leads
GLM-4.5-Air: 36.2 (#170), Llama 2-13B: 31.1 (#229)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Math | 1396 | 1065 |
| Omni-MATH | 39.1% | — |
| GSM8K | — | 36.9% |
Knowledge GLM-4.5-Air leads
GLM-4.5-Air: 35.0 (#191), Llama 2-13B: 28.1 (#249)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1370 | 1030 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |
Multimodal Not comparable
GLM-4.5-Air: —, Llama 2-13B: —
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| ScienceQA | — | 55.8% |
Multilingual GLM-4.5-Air leads
GLM-4.5-Air: 49.1 (#135), Llama 2-13B: 26.5 (#279)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1366 | 1024 |
| LMArena Chinese | 1426 | 1001 |
| LMArena French | 1399 | 1044 |
| LMArena German | 1377 | 1009 |
| LMArena Japanese | 1348 | 894 |
| LMArena Korean | 1308 | 953 |
| LMArena Russian | 1373 | 1055 |
| LMArena Spanish | 1386 | 1087 |
Instruction Following GLM-4.5-Air leads
GLM-4.5-Air: 69.6 (#171), Llama 2-13B: 53.3 (#287)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1354 | 1045 |
| IFEval | 81.2% | — |
Long Context GLM-4.5-Air leads
GLM-4.5-Air: 41.6 (#135), Llama 2-13B: 32.3 (#269)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1366 | 1064 |
Writing & Preference GLM-4.5-Air leads
GLM-4.5-Air: 55.9 (#139), Llama 2-13B: 29.8 (#289)
| Benchmark | GLM-4.5-Air | Llama 2-13B |
|---|---|---|
| LMArena Text | 1384 | 1084 |
| LMArena Creative Writing | 1343 | 1047 |
| LMArena Multi-Turn | 1371 | 1050 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Llama 2-13B?
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 29.6 on the Noometry Index.
Is GLM-4.5-Air or Llama 2-13B better for coding?
GLM-4.5-Air scores higher on coding benchmarks: 33.3 versus 30.9 in the Noometry coding category.
How many benchmarks do GLM-4.5-Air and Llama 2-13B share?
17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Llama 2-13B has 32.