Model comparison
GLM-4.5 vs Llama 2-70B
GLM-4.5 is the stronger model overall, scoring 42.0 to 24.4 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Llama 2-70B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.5 leads 39.0 to 8.1.
Side by side
| GLM-4.5 | Llama 2-70B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 42.0 | 24.4 |
| Released | 2025-07-27 | 2023-07-18 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 35 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Llama 2-70B: 31.4 (#286)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Coding | 1434 | 1079 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Llama 2-70B: 14.4 (#325)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1073 |
| Kagi LLM Benchmark | 57.9% | — |
| DTBench | — | 41.6% |
| BIG-Bench Hard | — | 64.9% |
| CommonsenseQA 2.0 | — | 50% |
| Epoch Capabilities Index | — | 113.79 |
| ForecastBench | — | 51.4 |
| HellaSwag | — | 85.3% |
| LAMBADA | — | 78.9% |
| PIQA | — | 82.8% |
| WinoGrande | — | 80.2% |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Llama 2-70B: 8.1 (#326)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Math | 1427 | 1091 |
| OTIS Mock AIME 2024-2025 | — | 0% |
| MATH Level 5 | — | 3.3% |
| GSM8K | — | 69.6% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), Llama 2-70B: 7.4 (#310)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Expert | 1433 | 1039 |
| GPQA Diamond | — | 26.3% |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 88.6% |
| MMLU | — | 69.9% |
| OpenBookQA | — | 60.2% |
| TriviaQA | — | 87.6% |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Llama 2-70B: 27.7 (#274)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Non-English | 1417 | 1045 |
| LMArena Chinese | 1465 | 995 |
| LMArena French | 1418 | 1090 |
| LMArena German | 1407 | 1041 |
| LMArena Japanese | 1415 | 927 |
| LMArena Korean | 1380 | 964 |
| LMArena Russian | 1414 | 1083 |
| LMArena Spanish | 1454 | 1143 |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Llama 2-70B: 54.9 (#278)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1071 |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#201), Llama 2-70B: 32.3 (#270)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Longer Query | 1412 | 1062 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Llama 2-70B: 32.3 (#279)
| Benchmark | GLM-4.5 | Llama 2-70B |
|---|---|---|
| LMArena Text | 1430 | 1115 |
| LMArena Creative Writing | 1395 | 1075 |
| LMArena Multi-Turn | 1415 | 1088 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Llama 2-70B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 24.4 on the Noometry Index.
Is GLM-4.5 or Llama 2-70B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 31.4 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Llama 2-70B share?
17 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 2-70B has 35.