Compare AI models
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 120B | 30B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 1M | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.08DekaLLM | $0.045Wafer |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.40DeepInfra | $0.13Wafer |
| Benchmarks | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 60.5% | 51.6% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 79.2% | 75.4% |
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 54% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | 36 | — |
| Overview | ||
| Company | NVIDIA | NVIDIA |
| Release date | Mar 11 2026 | Aug 11 2026 |
| Access | Open Source | Open Source |
| Model details | View model | View model |
Other comparisons
Nemotron 3 SupervsClaude Haiku 5.5Nemotron 3.5 LightningvsClaude Haiku 5.5Nemotron 3 SupervsGPT-6.1 SolNemotron 3.5 LightningvsGPT-6.1 SolNemotron 3 SupervsGemini 4 ArgonNemotron 3.5 LightningvsGemini 4 ArgonNemotron 3 SupervsMuse Spark 1.3Nemotron 3.5 LightningvsMuse Spark 1.3Nemotron 3 SupervsGrok 4.7Nemotron 3.5 LightningvsGrok 4.7Nemotron 3 SupervsDeepSeek-V4.1-FlashNemotron 3.5 LightningvsDeepSeek-V4.1-FlashFrequently asked questions
Nemotron 3 Super leads Nemotron 3.5 Lightning on 2 of the 2 benchmarks they both report (SWE-Bench Verified, GPQA Diamond). Nemotron 3 Super shipped 153 days before Nemotron 3.5 Lightning, so benchmark comparisons should account for the intervening progress.
Nemotron 3 Super has 120B parameters, while Nemotron 3.5 Lightning has 30B. Context windows are 1M (Nemotron 3 Super) vs 1M (Nemotron 3.5 Lightning).
On SWE-Bench Verified, Nemotron 3 Super leads at 60.5% vs Nemotron 3.5 Lightning at 51.6%. On GPQA Diamond, Nemotron 3 Super leads at 79.2% vs Nemotron 3.5 Lightning at 75.4%.