Model comparison
GLM-5.3-Flash vs Nemotron 3 Ultra
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.5 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Nemotron 3 Ultra in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 35.3.
- The biggest single-benchmark swing is APEX-Agents: 52.8% for GLM-5.3-Flash and 22.7% for Nemotron 3 Ultra.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.50 / $2.20 for Nemotron 3 Ultra.
- GLM-5.3-Flash accepts more context: 1M tokens versus 262K.
Side by side
| GLM-5.3-Flash | Nemotron 3 Ultra | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 51.8 | 42.5 |
| Released | 2026-08-20 | 2026-06-04 |
| Weights | Open | Open |
| Context window | 1M | 262K |
| Max output | 131K | 128K |
| Input $ / M tokens | $0.15 | $0.50 |
| Output $ / M tokens | $0.50 | $2.20 |
| Results tracked | 40 | 30 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#31), Nemotron 3 Ultra: 38.1 (#182)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| FrontierCode | 31.8% | 13.6% |
| SciCode | 51.6% | 40.3% |
| LMArena Coding | 1508 | 1468 |
| DeepSWE | 63.4% | — |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| WeirdML | — | 43.5% |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use GLM-5.3-Flash leads
GLM-5.3-Flash: 34.2 (#47), Nemotron 3 Ultra: 23.4 (#126)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| APEX-Agents | 52.8% | 22.7% |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 48.0 (#42), Nemotron 3 Ultra: 31.0 (#82)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| CritPt | 15.4% | 3.1% |
| Chess Puzzles | 14% | 12% |
| LMArena Hard Prompts | 1491 | 1452 |
| Mystery Game Puzzles | 8% | 20% |
| Epoch Capabilities Index | 151.88 | 146.17 |
| ARC-AGI-2 | 65.8% | — |
| ARC-AGI-1 | 91% | — |
| DTBench | — | 90.1% |
| LMCA | — | 36.9% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.3 (#47), Nemotron 3 Ultra: 35.3 (#187)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 86.7% |
| ProofBench | 21% | 2% |
| LMArena Math | 1500 | 1457 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#36), Nemotron 3 Ultra: 52.5 (#61)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| GPQA Diamond | 90.2% | 85.4% |
| LMArena Expert | 1513 | 1472 |
Multimodal Not comparable
GLM-5.3-Flash: 42.8 (#27), Nemotron 3 Ultra: —
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| LMArena Vision | 1296 | — |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.0 (#25), Nemotron 3 Ultra: 53.5 (#64)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| LMArena Non-English | 1462 | 1427 |
| LMArena Chinese | 1527 | 1497 |
| LMArena French | 1496 | 1472 |
| LMArena German | 1470 | 1471 |
| LMArena Korean | 1446 | 1386 |
| LMArena Russian | 1469 | 1417 |
| LMArena Spanish | 1471 | 1454 |
| LMArena Japanese | 1429 | — |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.5 (#20), Nemotron 3 Ultra: 74.7 (#88)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| LMArena Instruction Following | 1478 | 1418 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.4 (#39), Nemotron 3 Ultra: 43.9 (#81)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| LMArena Longer Query | 1482 | 1437 |
Writing & Preference Too close to call
GLM-5.3-Flash: 65.3 (#50), Nemotron 3 Ultra: 66.3 (#36)
| Benchmark | GLM-5.3-Flash | Nemotron 3 Ultra |
|---|---|---|
| LMArena Text | 1471 | 1445 |
| LMArena Creative Writing | 1442 | 1398 |
| LMArena Multi-Turn | 1467 | 1411 |
| EQ-Bench Creative Writing | — | 1692 |
Frequently asked questions
Is GLM-5.3-Flash better than Nemotron 3 Ultra?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.5 on the Noometry Index.
Which is cheaper, GLM-5.3-Flash or Nemotron 3 Ultra?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Nemotron 3 Ultra lists at $0.50 and $2.20.
Is GLM-5.3-Flash or Nemotron 3 Ultra better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 38.1 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 262K.
How many benchmarks do GLM-5.3-Flash and Nemotron 3 Ultra share?
26 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Nemotron 3 Ultra has 30.