Model comparison
GPT-5.2 Pro vs Nemotron 3 Super
GPT-5.2 Pro is the stronger model overall, scoring 52.2 to 39.6 on the Noometry Index. Nemotron 3 Super costs 335× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
NVIDIASummary
- They share 1 benchmark with published results for both. GPT-5.2 Pro scores higher in 2 categories and Nemotron 3 Super in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.2 Pro leads 51.8 to 17.9.
- The biggest single-benchmark swing is NYT Connections (extended): 79.3% for GPT-5.2 Pro and 15.4% for Nemotron 3 Super.
- Nemotron 3 Super is cheaper at $0.08 / $0.45 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- GPT-5.2 Pro accepts more context: 400K tokens versus 262K.
- Nemotron 3 Super has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Pro | Nemotron 3 Super | |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 52.2 | 39.6 |
| Released | 2025-12-11 | 2026-03-11 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $21 | $0.08 |
| Output $ / M tokens | $168 | $0.45 |
| Results tracked | 8 | 21 |
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Category by category
Coding Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 38.9 (#153)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| SciCode | — | 36% |
| WeirdML | — | 38% |
| LMArena Coding | — | 1403 |
| ALE-Bench | — | 213.9 |
Reasoning GPT-5.2 Pro leads
GPT-5.2 Pro: 51.8 (#31), Nemotron 3 Super: 17.9 (#274)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| NYT Connections (extended) | 79.3% | 15.4% |
| ARC-AGI-2 | 54.2% | — |
| SimpleBench | 57.4% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | — | 3.1% |
| LMArena Hard Prompts | — | 1386 |
| Epoch Capabilities Index | 155.41 | — |
Math GPT-5.2 Pro leads
GPT-5.2 Pro: 64.8 (#23), Nemotron 3 Super: 37.6 (#95)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| FrontierMath (Tiers 1-3) | 74% | — |
| FrontierMath Tier 4 | 46% | — |
| MathArena Final-Answer Competitions | — | 60.4% |
| LMArena Math | — | 1381 |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 38.2 (#136)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| LMArena Expert | — | 1397 |
Multilingual Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 48.6 (#139)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| LMArena Non-English | — | 1356 |
| LMArena Chinese | — | 1430 |
| LMArena French | — | 1404 |
| LMArena German | — | 1341 |
| LMArena Russian | — | 1336 |
| LMArena Spanish | — | 1417 |
Instruction Following Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 71.4 (#149)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| LMArena Instruction Following | — | 1347 |
Long Context Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 41.5 (#134)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| LMArena Longer Query | — | 1362 |
Writing & Preference Not comparable
GPT-5.2 Pro: —, Nemotron 3 Super: 56.1 (#135)
| Benchmark | GPT-5.2 Pro | Nemotron 3 Super |
|---|---|---|
| LMArena Text | — | 1378 |
| LMArena Creative Writing | — | 1317 |
| LMArena Multi-Turn | — | 1369 |
Frequently asked questions
Is GPT-5.2 Pro better than Nemotron 3 Super?
GPT-5.2 Pro is the stronger model overall, scoring 52.2 to 39.6 on the Noometry Index. Nemotron 3 Super costs 335× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 Pro or Nemotron 3 Super?
Nemotron 3 Super is cheaper. It lists at $0.08 per million input tokens and $0.45 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
GPT-5.2 Pro does, with 400K tokens against 262K.
How many benchmarks do GPT-5.2 Pro and Nemotron 3 Super share?
1 benchmark has published results for both models. GPT-5.2 Pro has 8 scored results on Noometry and Nemotron 3 Super has 21.