Muse Spark 1.1vsNemotron 3 Ultra
Muse Spark 1.1 | Nemotron 3 Ultra | |
|---|---|---|
| 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. | — | 550B |
| 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. | $1.25 | — |
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. | $4.25 | — |
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. | — | $0.50DeepInfra |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $2.20DeepInfra |
| Benchmarks | ||
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. | 62.1% | 26.7% |
| BenchmarksPublished by one model only | ||
SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | 61.5% | — |
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. | — | 71.9% |
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | 53.3% | — |
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. | 80% | — |
MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | 88.1% | — |
JobBenchProfessional tool use — Tests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better. | 54.7% | — |
Toolathlon-VerifiedPersonal tool use — Tests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better. | 75.6% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 44.4% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 86.7% |
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. | 80.8% | — |
Finance Agent v2Agentic financial analysis — Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 57.2% | — |
Harvey's Legal Agent BenchmarkAgentic legal work — Harvey's test of whether an AI agent can complete real legal work — drafting and reviewing documents, working with spreadsheets and presentations, and navigating files the way a lawyer's assistant would. Higher is better. | 20% | — |
TaxEval v2Tax questions — A set of real tax questions created by Vals AI — can the AI give accurate answers about tax rules and filings? Higher is better. | 79.72% | — |
MedScribeMedical admin work — Can the AI support doctors with their administrative work, like notes and paperwork? Created by Vals AI. Higher is better. | 88.89% | — |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | — | 48 |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | 88.4% | — |
BabyVisionVisual reasoning — Tests core visual reasoning — seeing and understanding images the way even young children can, which AIs often find surprisingly hard. Higher is better. | 76.3% | — |
| Overview | ||
| Company | Meta | NVIDIA |
| Release date | Jul 9 2026 | Jun 4 2026 |
| Access | Proprietary | Open Source |
Other comparisons
Frequently asked questions
Muse Spark 1.1 leads Nemotron 3 Ultra on 1 of the 1 benchmark they both report (Humanity's Last Exam). Only Muse Spark 1.1 has a verified first-party API price: $1.25 per million input tokens and $4.25 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Ultra. Nemotron 3 Ultra shipped 35 days before Muse Spark 1.1, so benchmark comparisons should account for the intervening progress.
Muse Spark 1.1 is proprietary, while Nemotron 3 Ultra is open source.
On Humanity's Last Exam · with tools, Muse Spark 1.1 leads at 62.1% vs Nemotron 3 Ultra at 26.7%.
Muse Spark 1.1 was released by Meta on Jul 9 2026.
Nemotron 3 Ultra was released by NVIDIA on Jun 4 2026.
Muse Spark 1.1 leads on Humanity's Last Exam · with tools — Muse Spark 1.1 62.1% vs Nemotron 3 Ultra 26.7%.
Only Muse Spark 1.1 has a verified first-party API price: $1.25 per million input tokens and $4.25 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Ultra. Rates are pay-as-you-go API prices verified on August 18, 2026.
Muse Spark 1.1 is a proprietary model released by Meta. Nemotron 3 Ultra is an open source model released by NVIDIA.