Model comparison
GLM-4.5-Air vs Llama2 70b Steerlm Chat
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 31.8 on the Noometry Index.
Last verified . 9 shared benchmarks.
NVIDIASummary
- They share 9 benchmarks with published results for both. GLM-4.5-Air scores higher in 7 categories and Llama2 70b Steerlm Chat in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5-Air leads 55.9 to 31.6.
Side by side
| GLM-4.5-Air | Llama2 70b Steerlm Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 38.9 | 31.8 |
| Released | 2025-07-20 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.20 | — |
| Output $ / M tokens | $1.10 | — |
| Results tracked | 27 | 9 |
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Category by category
Coding GLM-4.5-Air leads
GLM-4.5-Air: 33.3 (#259), Llama2 70b Steerlm Chat: 29.9 (#300)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Coding | 1397 | 1025 |
| GSO | 2.9% | — |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), Llama2 70b Steerlm Chat: 20.0 (#246)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1047 |
| Kagi LLM Benchmark | 43% | — |
| ForecastBench | 59.2 | — |
Math GLM-4.5-Air leads
GLM-4.5-Air: 36.2 (#170), Llama2 70b Steerlm Chat: 31.3 (#226)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | 1396 | 1072 |
| Omni-MATH | 39.1% | — |
Knowledge Not comparable
GLM-4.5-Air: 35.0 (#191), Llama2 70b Steerlm Chat: —
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
| LMArena Expert | 1370 | — |
Multilingual GLM-4.5-Air leads
GLM-4.5-Air: 49.1 (#135), Llama2 70b Steerlm Chat: 28.8 (#270)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | 1366 | 1063 |
| LMArena Chinese | 1426 | — |
| LMArena French | 1399 | — |
| LMArena German | 1377 | — |
| LMArena Japanese | 1348 | — |
| LMArena Korean | 1308 | — |
| LMArena Russian | 1373 | — |
| LMArena Spanish | 1386 | — |
Instruction Following GLM-4.5-Air leads
GLM-4.5-Air: 69.6 (#171), Llama2 70b Steerlm Chat: 54.2 (#279)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | 1354 | 1060 |
| IFEval | 81.2% | — |
Long Context GLM-4.5-Air leads
GLM-4.5-Air: 41.6 (#135), Llama2 70b Steerlm Chat: 30.4 (#288)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | 1366 | 998 |
Writing & Preference GLM-4.5-Air leads
GLM-4.5-Air: 55.9 (#139), Llama2 70b Steerlm Chat: 31.6 (#283)
| Benchmark | GLM-4.5-Air | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | 1384 | 1098 |
| LMArena Creative Writing | 1343 | 1091 |
| LMArena Multi-Turn | 1371 | 1058 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Llama2 70b Steerlm Chat?
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 31.8 on the Noometry Index.
Is GLM-4.5-Air or Llama2 70b Steerlm Chat better for coding?
GLM-4.5-Air scores higher on coding benchmarks: 33.3 versus 29.9 in the Noometry coding category.
How many benchmarks do GLM-4.5-Air and Llama2 70b Steerlm Chat share?
9 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Llama2 70b Steerlm Chat has 9.