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. | 128k | 400k |
| 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. | — | 45% |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 46% |
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% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 76% | — |
| Overview | ||
| Company | NVIDIA | OpenAI |
| Release date | Apr 7 2025 | Dec 18 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Llama Nemotron Ultra 253BvsClaude Fable 5.2GPT-5.2-CodexvsClaude Fable 5.2Llama Nemotron Ultra 253BvsGemini 4 CarbonGPT-5.2-CodexvsGemini 4 CarbonLlama Nemotron Ultra 253BvsMuse EmberGPT-5.2-CodexvsMuse EmberLlama Nemotron Ultra 253BvsGrok 4.7GPT-5.2-CodexvsGrok 4.7Llama Nemotron Ultra 253BvsDeepSeek-V4.1-Flash-1017GPT-5.2-CodexvsDeepSeek-V4.1-Flash-1017Llama Nemotron Ultra 253BvsMistral Large 4GPT-5.2-CodexvsMistral Large 4Frequently asked questions
Llama Nemotron Ultra 253B and GPT-5.2-Codex don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Llama Nemotron Ultra 253B shipped 255 days before GPT-5.2-Codex, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Llama Nemotron Ultra 253B) vs 400k (GPT-5.2-Codex). Llama Nemotron Ultra 253B is open weight, while GPT-5.2-Codex is closed.
Direct benchmark comparisons are unavailable — Llama Nemotron Ultra 253B and GPT-5.2-Codex don't publish scores on any of the same benchmarks.