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—
Benchmarks
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.
51.78%54%
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better.
67.72%79.8%
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.
66.7%73%
Overview
CompanyNVIDIASpaceXSI
Release dateOct 15 2026May 18 2026
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

Composer 2.5 leads Nemotron 3.5 Super VL on 3 of the 3 benchmarks they both report (SWE-Bench Pro, SWE-Bench Multilingual, Terminal-Bench 2.1). Composer 2.5 shipped 150 days before Nemotron 3.5 Super VL, so benchmark comparisons should account for the intervening progress.

Nemotron 3.5 Super VL is open weight, while Composer 2.5 is closed.

On SWE-Bench Pro, Composer 2.5 leads at 54% vs Nemotron 3.5 Super VL at 51.78%. On SWE-Bench Multilingual, Composer 2.5 leads at 79.8% vs Nemotron 3.5 Super VL at 67.72%. On Terminal-Bench 2.1, Composer 2.5 leads at 73% vs Nemotron 3.5 Super VL at 66.7%.