Model comparison
GLM-4.7 vs Llama2 70b Steerlm Chat
GLM-4.7 is the stronger model overall, scoring 41.7 to 31.2 on the Noometry Index.
Last verified . 9 shared benchmarks.
NVIDIASummary
- They share 9 benchmarks with published results for both. GLM-4.7 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-4.7 leads 61.1 to 31.8.
Side by side
| GLM-4.7 | Llama2 70b Steerlm Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 41.7 | 31.2 |
| Released | 2025-12-22 | — |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 36 | 9 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 43.6 (#74), Llama2 70b Steerlm Chat: 29.3 (#295)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Coding | 1454 | 1025 |
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.4 (#96), Llama2 70b Steerlm Chat: —
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 23.7 (#161), Llama2 70b Steerlm Chat: 19.1 (#245)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1047 |
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| Epoch Capabilities Index | 143.53 | — |
Math GLM-4.7 leads
GLM-4.7: 37.7 (#92), Llama2 70b Steerlm Chat: 28.8 (#223)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | 1423 | 1072 |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Not comparable
GLM-4.7: 47.0 (#74), Llama2 70b Steerlm Chat: —
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| LMArena Expert | 1424 | — |
Multilingual GLM-4.7 leads
GLM-4.7: 53.0 (#75), Llama2 70b Steerlm Chat: 28.9 (#265)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | 1417 | 1064 |
| LMArena Chinese | 1495 | — |
| LMArena French | 1432 | — |
| LMArena German | 1426 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1423 | — |
| LMArena Spanish | 1433 | — |
Instruction Following GLM-4.7 leads
GLM-4.7: 74.6 (#90), Llama2 70b Steerlm Chat: 54.5 (#274)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | 1411 | 1061 |
Long Context GLM-4.7 leads
GLM-4.7: 42.8 (#111), Llama2 70b Steerlm Chat: 30.4 (#283)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | 1432 | 998 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference GLM-4.7 leads
GLM-4.7: 61.1 (#89), Llama2 70b Steerlm Chat: 31.8 (#278)
| Benchmark | GLM-4.7 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | 1436 | 1098 |
| LMArena Creative Writing | 1401 | 1091 |
| LMArena Multi-Turn | 1446 | 1058 |
| EQ-Bench Creative Writing | 1413 | — |
Frequently asked questions
Is GLM-4.7 better than Llama2 70b Steerlm Chat?
GLM-4.7 is the stronger model overall, scoring 41.7 to 31.2 on the Noometry Index.
Is GLM-4.7 or Llama2 70b Steerlm Chat better for coding?
GLM-4.7 scores higher on coding benchmarks: 43.6 versus 29.3 in the Noometry coding category.
How many benchmarks do GLM-4.7 and Llama2 70b Steerlm Chat share?
9 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Llama2 70b Steerlm Chat has 9.