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. | 816B | 9B |
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 | — |
| These models have no shared benchmark scores. | ||
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% |
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. | 60% | — |
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% |
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. | 76.4% | — |
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. | 89.2% | — |
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. | 61.8% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 64% |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 1401 | — |
| Overview | ||
| Company | Meta | NVIDIA |
| Release date | Oct 15 2026 | Aug 18 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Muse Spark OpenvsClaude Haiku 5.5Nemotron Nano 2vsClaude Haiku 5.5Muse Spark OpenvsGPT-6.1 SolNemotron Nano 2vsGPT-6.1 SolMuse Spark OpenvsGemini 4 ArgonNemotron Nano 2vsGemini 4 ArgonMuse Spark OpenvsGrok 4.7Nemotron Nano 2vsGrok 4.7Muse Spark OpenvsDeepSeek-V4.1-FlashNemotron Nano 2vsDeepSeek-V4.1-FlashMuse Spark OpenvsMistral Large 4Nemotron Nano 2vsMistral Large 4Frequently asked questions
Muse Spark Open and Nemotron Nano 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Nemotron Nano 2 shipped 423 days before Muse Spark Open, so benchmark comparisons should account for the intervening progress.
Muse Spark Open has 816B parameters, while Nemotron Nano 2 has 9B.
Direct benchmark comparisons are unavailable — Muse Spark Open and Nemotron Nano 2 don't publish scores on any of the same benchmarks.