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. | — | 120B |
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 |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $3.00 | — |
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. | $15.00 | — |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.30 | — |
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. | $3.00Amazon Bedrock | $0.08DekaLLM |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $15.00Amazon Bedrock | $0.40DeepInfra |
| 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. | 79% | 54% |
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. | 77.2% | 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. | 83.4% | 79.2% |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 39% | — |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 13.6% | — |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 61.4% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | — | 36 |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | 68% | — |
| Overview | ||
| Company | Anthropic | NVIDIA |
| Release date | Sep 29 2025 | Mar 11 2026 |
| Access | Closed | Open Source |
| Model details | View model | View model |
Other comparisons
Claude Sonnet 4.5vsGPT-6.1 SolNemotron 3 SupervsGPT-6.1 SolClaude Sonnet 4.5vsGemini 4 ArgonNemotron 3 SupervsGemini 4 ArgonClaude Sonnet 4.5vsMuse Spark 1.3Nemotron 3 SupervsMuse Spark 1.3Claude Sonnet 4.5vsGrok 4.7Nemotron 3 SupervsGrok 4.7Claude Sonnet 4.5vsDeepSeek-V4.1-FlashNemotron 3 SupervsDeepSeek-V4.1-FlashClaude Sonnet 4.5vsMistral Large 4Nemotron 3 SupervsMistral Large 4Frequently asked questions
Claude Sonnet 4.5 leads Nemotron 3 Super on 3 of the 3 benchmarks they both report (BullshitBench v2, SWE-Bench Verified, GPQA Diamond). Only Claude Sonnet 4.5 has a verified first-party API price: $3.00 per million input tokens and $15.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Super. Claude Sonnet 4.5 shipped 163 days before Nemotron 3 Super, so benchmark comparisons should account for the intervening progress.
Claude Sonnet 4.5 is closed, while Nemotron 3 Super is open source.
On BullshitBench v2, Claude Sonnet 4.5 leads at 79% vs Nemotron 3 Super at 54%. On SWE-Bench Verified, Claude Sonnet 4.5 leads at 77.2% vs Nemotron 3 Super at 60.5%. On GPQA Diamond, Claude Sonnet 4.5 leads at 83.4% vs Nemotron 3 Super at 79.2%.