Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 30B | — |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 1M | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.05Novita | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.20Novita | — |
| $20.00Novita · fp4 | — | |
| These models have no shared benchmark scores. | ||
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. | 28% | — |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | 68.3% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 73% | — |
| Overview | ||
| Company | NVIDIA | OpenAI |
| Release date | Dec 15 2025 | Feb 27 2025 |
| Access | Open Source | Closed |
| Model details | View model | View model |
Other comparisons
Nemotron 3 NanovsClaude Haiku 5.5GPT-4.5vsClaude Haiku 5.5Nemotron 3 NanovsGemini 4 ArgonGPT-4.5vsGemini 4 ArgonNemotron 3 NanovsMuse Spark OpenGPT-4.5vsMuse Spark OpenNemotron 3 NanovsGrok 4.7GPT-4.5vsGrok 4.7Nemotron 3 NanovsDeepSeek-V4.1-Flash-1017GPT-4.5vsDeepSeek-V4.1-Flash-1017Nemotron 3 NanovsMistral Large 4GPT-4.5vsMistral Large 4Frequently asked questions
Nemotron 3 Nano and GPT-4.5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. GPT-4.5 shipped 291 days before Nemotron 3 Nano, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Nemotron 3 Nano) vs 128k (GPT-4.5). Nemotron 3 Nano is open source, while GPT-4.5 is closed.
Direct benchmark comparisons are unavailable — Nemotron 3 Nano and GPT-4.5 don't publish scores on any of the same benchmarks.