Nemotron Nano 2vsgpt-oss-20b
Nemotron Nano 2 | gpt-oss-20b | |
|---|---|---|
| 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. | 9B | 21B |
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. | — | 128k |
| 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. | — | $0.02Darkbloom |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.10Darkbloom |
| 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% | 71.5% |
| BenchmarksPublished by one model only | ||
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. | — | 60.7% |
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. | 71.1% | — |
Humanity's Last Exam · no toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | — | 10.9% |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 17.3% |
MMLUGeneral knowledge — A 57-subject multiple-choice exam — history, law, medicine, maths — that was the standard measure of how much a model knows from 2020 until roughly 2024, when frontier scores crowded into the high 80s and labs moved on to harder tests. The scores here were published years apart under different testing setups, so read them as a historical record rather than a like-for-like ranking. Higher is better. | — | 85.3% |
| Overview | ||
| Company | NVIDIA | OpenAI |
| Release date | Aug 18 2025 | Aug 5 2025 |
| Access | Open Weight | Open Weight |
Other comparisons
Nemotron Nano 2vsClaude Opus 5gpt-oss-20bvsClaude Opus 5Nemotron Nano 2vsGemini 3.7 Flashgpt-oss-20bvsGemini 3.7 FlashNemotron Nano 2vsMuse Glimmergpt-oss-20bvsMuse GlimmerNemotron Nano 2vsGrok 4.6gpt-oss-20bvsGrok 4.6Nemotron Nano 2vsDeepSeek-V4-Pro-0813gpt-oss-20bvsDeepSeek-V4-Pro-0813Nemotron Nano 2vsMistral Medium 3.5gpt-oss-20bvsMistral Medium 3.5
Frequently asked questions
gpt-oss-20b leads Nemotron Nano 2 on 1 of the 1 benchmark they both report (GPQA Diamond). gpt-oss-20b shipped 13 days before Nemotron Nano 2, so benchmark comparisons should account for the intervening progress.
Nemotron Nano 2 has 9B parameters, while gpt-oss-20b has 21B.
On GPQA Diamond, gpt-oss-20b leads at 71.5% vs Nemotron Nano 2 at 64%.
Nemotron Nano 2 was released by NVIDIA on Aug 18 2025.
gpt-oss-20b was released by OpenAI on Aug 5 2025.
gpt-oss-20b leads on GPQA Diamond — Nemotron Nano 2 64% vs gpt-oss-20b 71.5%.