Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 253B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 1M | 128k |
| These models have no shared benchmark scores. | ||
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. | 95.5% | — |
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. | — | 66.3% |
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. | 88% | — |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | 88% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 88% | — |
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. | 64.5% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 76% |
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. | 85% | — |
| Overview | ||
| Company | Anthropic | NVIDIA |
| Release date | Jun 9 2026 | Apr 8 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude Mythos 5vsGPT-6.1 SolLlama Nemotron Ultra 253BvsGPT-6.1 SolClaude Mythos 5vsGemini 4 ArgonLlama Nemotron Ultra 253BvsGemini 4 ArgonClaude Mythos 5vsMuse Spark OpenLlama Nemotron Ultra 253BvsMuse Spark OpenClaude Mythos 5vsGrok 4.7Llama Nemotron Ultra 253BvsGrok 4.7Claude Mythos 5vsDeepSeek-V4.1-Flash-1017Llama Nemotron Ultra 253BvsDeepSeek-V4.1-Flash-1017Claude Mythos 5vsMistral Large 4Llama Nemotron Ultra 253BvsMistral Large 4Frequently asked questions
Claude Mythos 5 and Llama Nemotron Ultra 253B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Llama Nemotron Ultra 253B shipped 427 days before Claude Mythos 5, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5) vs 128k (Llama Nemotron Ultra 253B). Claude Mythos 5 is closed, while Llama Nemotron Ultra 253B is open weight.
Direct benchmark comparisons are unavailable — Claude Mythos 5 and Llama Nemotron Ultra 253B don't publish scores on any of the same benchmarks.