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. | 9B | — |
| 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. | — | $0.50 |
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. | — | $3.00 |
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. | — | $0.325Alibaba |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $1.95Alibaba |
| Benchmarks | ||
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. | 5% | 72% |
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. | — | 78.8% |
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 · 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. | — | 28.8% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 64% | — |
| Overview | ||
| Company | NVIDIA | Qwen |
| Release date | Aug 18 2025 | Apr 2 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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Qwen3.6-Plus leads Nemotron Nano 2 on 1 of the 1 benchmark they both report (BullshitBench v2). Only Qwen3.6-Plus has a verified first-party API price: $0.50 per million input tokens and $3.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron Nano 2. Nemotron Nano 2 shipped 227 days before Qwen3.6-Plus, so benchmark comparisons should account for the intervening progress.
Nemotron Nano 2 is open weight, while Qwen3.6-Plus is closed.
On BullshitBench v2, Qwen3.6-Plus leads at 72% vs Nemotron Nano 2 at 5%.