Model comparison
GLM-4.5 vs Llama 3.1 Nemotron Ultra 253b v1
GLM-4.5 is the stronger model overall, scoring 42.0 to 36.7 on the Noometry Index.
Last verified . 10 shared benchmarks.
NVIDIASummary
- They share 10 benchmarks with published results for both. GLM-4.5 scores higher in 6 categories and Llama 3.1 Nemotron Ultra 253b v1 in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.5 leads 52.8 to 43.1.
Side by side
| GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 42.0 | 36.7 |
| Released | 2025-07-27 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 11 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Llama 3.1 Nemotron Ultra 253b v1: 38.4 (#177)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Coding | 1434 | 1312 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, Llama 3.1 Nemotron Ultra 253b v1: 15.7 (#149)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Llama 3.1 Nemotron Ultra 253b v1: 26.3 (#134)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1316 |
| Kagi LLM Benchmark | 57.9% | — |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Llama 3.1 Nemotron Ultra 253b v1: 37.5 (#152)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Math | 1427 | 1360 |
Knowledge Not comparable
GLM-4.5: 35.9 (#179), Llama 3.1 Nemotron Ultra 253b v1: —
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| LMArena Expert | 1433 | — |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Llama 3.1 Nemotron Ultra 253b v1: 43.1 (#187)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Non-English | 1417 | 1282 |
| LMArena Russian | 1414 | 1284 |
| LMArena Chinese | 1465 | — |
| LMArena French | 1418 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
| LMArena Spanish | 1454 | — |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Llama 3.1 Nemotron Ultra 253b v1: 69.0 (#178)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1308 |
Long Context Llama 3.1 Nemotron Ultra 253b v1 leads
GLM-4.5: 38.2 (#201), Llama 3.1 Nemotron Ultra 253b v1: 39.5 (#177)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Longer Query | 1412 | 1299 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Llama 3.1 Nemotron Ultra 253b v1: 52.2 (#175)
| Benchmark | GLM-4.5 | Llama 3.1 Nemotron Ultra 253b v1 |
|---|---|---|
| LMArena Text | 1430 | 1320 |
| LMArena Creative Writing | 1395 | 1314 |
| LMArena Multi-Turn | 1415 | 1317 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Llama 3.1 Nemotron Ultra 253b v1?
GLM-4.5 is the stronger model overall, scoring 42.0 to 36.7 on the Noometry Index.
Is GLM-4.5 or Llama 3.1 Nemotron Ultra 253b v1 better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 38.4 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Llama 3.1 Nemotron Ultra 253b v1 share?
10 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 3.1 Nemotron Ultra 253b v1 has 11.