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. | 8B/70B/405B | 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 | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.02DeepInfra | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.04DeepInfra | — |
| $6.00DeepInfra · fp8 | — | |
| 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. | 14% | — |
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 | Meta | NVIDIA |
| Release date | Jul 23 2024 | Apr 8 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.1vsClaude Haiku 5.5Llama Nemotron Ultra 253BvsClaude Haiku 5.5LLaMA 3.1vsGPT-6.1 SolLlama Nemotron Ultra 253BvsGPT-6.1 SolLLaMA 3.1vsGemini 4 ArgonLlama Nemotron Ultra 253BvsGemini 4 ArgonLLaMA 3.1vsGrok 4.7Llama Nemotron Ultra 253BvsGrok 4.7LLaMA 3.1vsDeepSeek-V4.1-Flash-1017Llama Nemotron Ultra 253BvsDeepSeek-V4.1-Flash-1017LLaMA 3.1vsMistral Large 4Llama Nemotron Ultra 253BvsMistral Large 4Frequently asked questions
LLaMA 3.1 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 3.1 shipped 259 days before Llama Nemotron Ultra 253B, so benchmark comparisons should account for the intervening progress.
LLaMA 3.1 has 8B/70B/405B parameters, while Llama Nemotron Ultra 253B has 253B. Context windows are 128k (LLaMA 3.1) vs 128k (Llama Nemotron Ultra 253B).
Direct benchmark comparisons are unavailable — LLaMA 3.1 and Llama Nemotron Ultra 253B don't publish scores on any of the same benchmarks.