Model comparison
GLM-4.5 vs Llama 2-13B
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GLM-4.5 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 leads 57.5 to 29.8.
Side by side
| GLM-4.5 | Llama 2-13B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 42.0 | 29.6 |
| 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 | 32 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Llama 2-13B: 30.9 (#291)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1434 | 1062 |
| 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 2-13B: 12.8 (#337)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1051 |
| Kagi LLM Benchmark | 57.9% | — |
| Chess Puzzles | — | 0% |
| DTBench | — | 42.2% |
| BIG-Bench Hard | — | 58.2% |
| Epoch Capabilities Index | — | 106.17 |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Llama 2-13B: 31.1 (#229)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Math | 1427 | 1065 |
| GSM8K | — | 36.9% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), Llama 2-13B: 28.1 (#249)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1433 | 1030 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |
Multimodal Not comparable
GLM-4.5: —, Llama 2-13B: —
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| ScienceQA | — | 55.8% |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Llama 2-13B: 26.5 (#279)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1417 | 1024 |
| LMArena Chinese | 1465 | 1001 |
| LMArena French | 1418 | 1044 |
| LMArena German | 1407 | 1009 |
| LMArena Japanese | 1415 | 894 |
| LMArena Korean | 1380 | 953 |
| LMArena Russian | 1414 | 1055 |
| LMArena Spanish | 1454 | 1087 |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Llama 2-13B: 53.3 (#287)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1045 |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#201), Llama 2-13B: 32.3 (#269)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1412 | 1064 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Llama 2-13B: 29.8 (#289)
| Benchmark | GLM-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Text | 1430 | 1084 |
| LMArena Creative Writing | 1395 | 1047 |
| LMArena Multi-Turn | 1415 | 1050 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Llama 2-13B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.6 on the Noometry Index.
Is GLM-4.5 or Llama 2-13B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 30.9 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Llama 2-13B share?
17 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 2-13B has 32.