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. | — | 4B |
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. | 2M | 256k |
| Benchmarks | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 64.7% | 72.41% |
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. | — | 59.5% |
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. | 36% | — |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 18.1% |
MATHReasoning — accuracy on the original competition mathematics test set | 91.8% | — |
IFBenchInstruction following — Tests whether the AI can follow detailed instructions and satisfy multiple constraints at once. Higher is better. | — | 77.94% |
SimpleQAKnowledge — accuracy on short, fact-seeking questions in the original SimpleQA set | 44.3% | — |
MMLU-ProKnowledge — accuracy on the ten-option MMLU-Pro benchmark | 79.1% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 72.7% | — |
| Overview | ||
| Company | NVIDIA | |
| Release date | Feb 5 2025 | Oct 16 2026 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
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Nemotron Labs Dory 1.0 4B leads Gemini 2.0 Pro on 1 of the 1 benchmark they both report (GPQA Diamond). Gemini 2.0 Pro shipped 618 days before Nemotron Labs Dory 1.0 4B, so benchmark comparisons should account for the intervening progress.
Context windows are 2M (Gemini 2.0 Pro) vs 256k (Nemotron Labs Dory 1.0 4B). Gemini 2.0 Pro is closed, while Nemotron Labs Dory 1.0 4B is open weight.
On GPQA Diamond, Nemotron Labs Dory 1.0 4B leads at 72.41% vs Gemini 2.0 Pro at 64.7%.