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. | — | 550B |
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 | ||
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. | $1.25Meta | $0.50DeepInfra |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $4.25Meta | $2.20DeepInfra |
| Benchmarks | ||
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. | 82.9% | 56.4% |
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. | 50% | — |
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. | 59.3% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 44.4% |
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. | — | 26.7% |
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% |
AA Intelligence IndexOverall intelligence — Artificial Analysis composite intelligence index across evals | — | 48 |
| Overview | ||
| Company | Meta | NVIDIA |
| Release date | Aug 5 2026 | Jun 4 2026 |
| Access | Closed | Open Source |
| Model details | View model | View model |
Other comparisons
Muse Spark 1.2vsClaude Opus 5.5Nemotron 3 UltravsClaude Opus 5.5Muse Spark 1.2vsGPT-6 SolNemotron 3 UltravsGPT-6 SolMuse Spark 1.2vsGemini 3.8 FlashNemotron 3 UltravsGemini 3.8 FlashMuse Spark 1.2vsGrok 4.7Nemotron 3 UltravsGrok 4.7Muse Spark 1.2vsDeepSeek-V4.1-FlashNemotron 3 UltravsDeepSeek-V4.1-FlashMuse Spark 1.2vsMistral Medium 3.5Nemotron 3 UltravsMistral Medium 3.5Frequently asked questions
Muse Spark 1.2 leads Nemotron 3 Ultra on 1 of the 1 benchmark they both report (Terminal-Bench 2.1). Nemotron 3 Ultra shipped 62 days before Muse Spark 1.2, so benchmark comparisons should account for the intervening progress.
Muse Spark 1.2 is closed, while Nemotron 3 Ultra is open source.
On Terminal-Bench 2.1, Muse Spark 1.2 leads at 82.9% vs Nemotron 3 Ultra at 56.4%.