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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.
70B—
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.
128k400k
Overview
CompanyNVIDIAOpenAI
Release dateOct 15 2024Nov 13 2025
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

Llama 3.1 Nemotron 70BvsClaude Fable 5.2GPT-5.1-Codex-MinivsClaude Fable 5.2Llama 3.1 Nemotron 70BvsGemini 4 CarbonGPT-5.1-Codex-MinivsGemini 4 CarbonLlama 3.1 Nemotron 70BvsMuse EmberGPT-5.1-Codex-MinivsMuse EmberLlama 3.1 Nemotron 70BvsGrok 4.7GPT-5.1-Codex-MinivsGrok 4.7Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017GPT-5.1-Codex-MinivsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsMistral Large 4GPT-5.1-Codex-MinivsMistral Large 4

Frequently asked questions

Llama 3.1 Nemotron 70B and GPT-5.1-Codex-Mini don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Llama 3.1 Nemotron 70B shipped 394 days before GPT-5.1-Codex-Mini, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (Llama 3.1 Nemotron 70B) vs 400k (GPT-5.1-Codex-Mini). Llama 3.1 Nemotron 70B is open weight, while GPT-5.1-Codex-Mini is closed.

Direct benchmark comparisons are unavailable — Llama 3.1 Nemotron 70B and GPT-5.1-Codex-Mini don't publish scores on any of the same benchmarks.