References 687% CONFIDENCEOverall confidence: 87%How well the pin's source and references back up its dates.Weighted average of how firmly 6 references, the source included, support the pin's start and end times; a reference counts half as much for every 180 days older than the newestShow all pins at 75% confidence or better

The first entry is always the pin's source. Overall confidence is a weighted average of how firmly each reference supports the start and end times used above; a reference counts half as much for every 180 days older than the newest.

• [1]90%
  huggingface.co/meta-llama/Llama-3.3-70B-Instruct

  huggingface.co· Posted Oct 12, 2026· Starts Dec 6, 2024 ✓· 73% of score

  Meta's model card lists 'Model Release Date: 70B Instruct: December 6, 2024'; TechCrunch's^[5] report is dated December 6, 2024 and OpenRouter^[6] lists meta-llama/llama-3.3-70b-instruct as created the same day.

• [2]70%
  Meta releases AI model 'Llama 3.3' - GIGAZINE

  gigazine.net· Published Dec 9, 2024· 5% of score

  Reproduces Meta's benchmark and pricing table: Llama 3.3 70B against Llama 3.1 70B and 405B, Amazon Nova Pro, Gemini Pro 1.5, GPT-4o and Claude 3.5 Sonnet, with a $0.1 input and $0.4 output per 1 million tokens row; notes training on over 15 trillion tokens to December 2023 and the 700 million monthly user cap.^[1]

• [3]70%
  Llama 3.3 70B is Here! 25x Cheaper than GPT-4o - Analytics Vidhya

  analyticsvidhya.com· Published Dec 9, 2024· 5% of score

  Secondary explainer: head-to-head with GPT-4o (IFEval 92.1 against 84.6, HumanEval 88.4 against 86.0, MMLU Pro 68.9 against 73.8), Artificial Analysis Quality Index 74 against 86 for o1-preview, and where to run it: Hugging Face^[1], Ollama (about 42 GB), Groq, Deep Infra, Hyperbolic, Fireworks and Together AI.

• [4]90%
  Llama 3.3 model card - meta-llama/llama-models

  github.com· Published Dec 6, 2024· 5% of score

  Meta's model card: 70B text-in text-out, 128k context, GQA, 15T+ pretraining tokens with a December 2023 cutoff, over 25M synthetic fine-tuning examples, 7.0M H100 GPU hours and 12.9 tons CO2eq location-based, eight supported languages, and the instruction-tuned table against Llama 3.1 8B, 70B and 405B.^[1]

• [5]85%
  Meta unveils a new, more efficient Llama model - TechCrunch

  techcrunch.com· Published Dec 6, 2024· 5% of score

  Same-day report by Kyle Wiggers: Meta says it delivers the performance of Llama 3.1 405B at lower cost, Ahmad Al-Dahle's chart against Gemini 1.5 Pro, GPT-4o and Nova Pro, the 700-million-user licence clause, more than 650 million Llama downloads, Meta AI near 600 million monthly users, and Llama 4 needing 10x the compute.^[1]

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