Model comparison
GLM-5.3-Flash vs Llama 3.1 Nemotron 70b Instruct
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 37.6 on the Noometry Index.
Last verified . 12 shared benchmarks.
NVIDIASummary
- They share 12 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Llama 3.1 Nemotron 70b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 34.1.
Side by side
| GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 51.8 | 37.6 |
| Released | 2026-08-20 | 2024-12-18 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.50 | — |
| Results tracked | 40 | 14 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#31), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Coding | 1508 | 1272 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| SciCode | 51.6% | — |
| BigCodeBench Instruct | — | 38.7% |
| BigCodeBench Complete | — | 48.2% |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use Not comparable
GLM-5.3-Flash: 34.2 (#47), Llama 3.1 Nemotron 70b Instruct: —
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 48.0 (#42), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1491 | 1266 |
| ARC-AGI-2 | 65.8% | — |
| ARC-AGI-1 | 91% | — |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.88 | — |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.3 (#47), Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Math | 1500 | 1271 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#36), Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Expert | 1513 | 1242 |
| GPQA Diamond | 90.2% | — |
Multimodal Not comparable
GLM-5.3-Flash: 42.8 (#27), Llama 3.1 Nemotron 70b Instruct: —
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Vision | 1296 | — |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.0 (#25), Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Non-English | 1462 | 1245 |
| LMArena Chinese | 1527 | 1263 |
| LMArena Russian | 1469 | 1227 |
| LMArena French | 1496 | — |
| LMArena German | 1470 | — |
| LMArena Japanese | 1429 | — |
| LMArena Korean | 1446 | — |
| LMArena Spanish | 1471 | — |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.5 (#20), Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Instruction Following | 1478 | 1252 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.4 (#39), Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Longer Query | 1482 | 1238 |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.3 (#50), Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)
| Benchmark | GLM-5.3-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Text | 1471 | 1283 |
| LMArena Creative Writing | 1442 | 1269 |
| LMArena Multi-Turn | 1467 | 1275 |
Frequently asked questions
Is GLM-5.3-Flash better than Llama 3.1 Nemotron 70b Instruct?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 37.6 on the Noometry Index.
Is GLM-5.3-Flash or Llama 3.1 Nemotron 70b Instruct better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 35.9 in the Noometry coding category.
How many benchmarks do GLM-5.3-Flash and Llama 3.1 Nemotron 70b Instruct share?
12 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.