Nemotron 3 SupervsQwen3-Coder
Nemotron 3 Super | Qwen3-Coder | |
|---|---|---|
| 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 | 480B |
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 | 256k |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $1.00 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $5.00 |
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. | — | $0.22Google |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $1.00DeepInfra |
| BenchmarksPublished by one model only | ||
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. | — | 20% |
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% | — |
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% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | 36 | — |
| Overview | ||
| Company | NVIDIA | Qwen |
| Release date | Mar 11 2026 | Jul 22 2025 |
| Access | Open Source | Open Weight |
Other comparisons
Frequently asked questions
Nemotron 3 Super and Qwen3-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3-Coder has a verified first-party API price: $1.00 per million input tokens and $5.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Super. Qwen3-Coder shipped 232 days before Nemotron 3 Super, so benchmark comparisons should account for the intervening progress.
Nemotron 3 Super has 120B parameters, while Qwen3-Coder has 480B. Context windows are 1M (Nemotron 3 Super) vs 256k (Qwen3-Coder). Nemotron 3 Super is open source, while Qwen3-Coder is open weight.
Direct benchmark comparisons are unavailable — Nemotron 3 Super and Qwen3-Coder don't publish scores on any of the same benchmarks.
Nemotron 3 Super was released by NVIDIA on Mar 11 2026.
Qwen3-Coder was released by Qwen on Jul 22 2025.
Only Qwen3-Coder has a verified first-party API price: $1.00 per million input tokens and $5.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Super. Rates are pay-as-you-go API prices verified on August 18, 2026.
Nemotron 3 Super has a 1M context window; Qwen3-Coder has 256k.
Nemotron 3 Super is an open source model released by NVIDIA. Qwen3-Coder is an open weight model released by Qwen.