# Llama 3.1 405B Instruct ![Organization](https://img.shields.io/badge/Org-Meta-0064e0) ![Parameters](https://img.shields.io/badge/Params-405B-1f6feb) ![Context](https://img.shields.io/badge/Context-128K%20tokens-1f6feb) ![License](https://img.shields.io/badge/License-Llama%203.1-d29922) ![Weights](https://img.shields.io/badge/Weights-Open-2da44e) ![Released](https://img.shields.io/badge/Released-Jul%202024-555) > **Quick answer:** Llama 3.1 405B Instruct is Meta's July 2024 largest open-weight model, scoring 96.9% on AI2 Reasoning Challenge, 88.6% on MMLU, 73.3% on MMLU-Pro, and 26.4% on BigCodeBench. With a 128K-token context window under the Llama 3.1 License, it was the first open-weight model to match GPT-4-class performance at the 400B+ parameter scale. ## At a Glance **Where Llama 3.1 405B leads** - 96.9% AI2 Reasoning Challenge — near-perfect scientific reasoning - 88.6% MMLU — matches GPT-4 Turbo (86.4%) at open-weight pricing - 73.3% MMLU-Pro — strong academic knowledge - Largest open-weight dense model at launch - 128K context window - Establishes frontier capability ceiling for open-weight models at launch **Where it lags** - Dense 405B: massive infrastructure requirement for self-hosting - Superseded by Llama 4 Maverick for most tasks at far lower cost - Text-only: no vision - March 2024 knowledge cutoff - 26.4% BigCodeBench — moderate coding performance **Best for:** Research requiring maximum open-weight capability; self-hosted frontier AI where data sovereignty is paramount; fine-tuning at maximum scale. ## What Llama 3.1 405B Instruct Is Llama 3.1 405B Instruct was the largest open-weight model available when released July 23, 2024 — and the first to directly compete with GPT-4 on MMLU. Its release was a landmark event: for the first time, teams could access GPT-4-class performance through self-hosted open weights. At 88.6% MMLU, the 405B surpassed the then-state-of-the-art GPT-4 Turbo (86.4%) on the primary academic knowledge benchmark. This performance came at substantial infrastructure cost: a dense 405B model requires multiple high-end GPUs for inference. For most production use cases, Llama 4 Maverick (17B active MoE, 1M context, better overall performance) is the recommended replacement. Llama 3.1 405B remains relevant for teams with specific requirements: maximum open-weight capability, dense architecture for quantisation research, or use cases where the Llama 3.1 instruction style has been validated in production. ## Specifications | Field | Value | |---|---| | Organization | Meta | | Parameters | 405B (dense) | | Context window | 128,000 tokens | | License | Llama 3.1 License | | HuggingFace | [meta-llama/Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) | | Release date | July 23, 2024 | | Knowledge cutoff | March 2024 | | Modality | Text only | ## Pricing Llama 3.1 405B is available as open weights under the Llama 3.1 License — free to self-host. Hosted API access via Together AI, Fireworks, and others at market rates. ## Public Benchmark Scores | Benchmark | Score | Source | Date | |---|---|---|---| | [AI2 Reasoning Challenge](/benchmarks/ai2-reasoning-challenge) | 96.9% | Benchgen evaluation | 2024-07 | | [MMLU](/benchmarks/mmlu) | 88.6% | Benchgen evaluation | 2024-07 | | [MMLU-Pro](/benchmarks/mmlu-pro) | 73.3% | Benchgen evaluation | 2024-07 | | [BigCodeBench](/benchmarks/bigcodebench) | 26.4% | Benchgen evaluation | 2024-07 | ## Llama 3.1 405B vs Alternatives | Model | MMLU | MMLU-Pro | Context | Weights | |---|---|---|---|---| | **Llama 3.1 405B Instruct** | 88.6% | 73.3% | 128K | Open (dense 405B) | | [Llama 3.1 70B Instruct](/models/meta/llama-3-1-70b-instruct) | 86.0% | — | 128K | Open (dense 70B) | | [Llama 4 Maverick](/models/meta/llama-4-maverick) | — | 80.5% | 1M | Open (17B active MoE) | | [GPT-4 Turbo](/models/openai/gpt-4-turbo) | 86.4% | — | 128K | Closed | Llama 4 Maverick (17B active MoE) achieves 80.5% MMLU-Pro vs Llama 3.1 405B's 73.3%, with a 1M context window, multimodal capability, and dramatically lower inference cost. For new deployments, Llama 4 Maverick is the recommended open-weight choice. ## Related Models & Benchmarks - Compare: [Llama 3.1 70B Instruct](/models/meta/llama-3-1-70b-instruct) · [Llama 4 Maverick](/models/meta/llama-4-maverick) · [DeepSeek-V3](/models/deepseek/deepseek-v3) - Benchmarks: [AI2 Reasoning Challenge](/benchmarks/ai2-reasoning-challenge) · [MMLU](/benchmarks/mmlu) · [MMLU-Pro](/benchmarks/mmlu-pro) ## Frequently Asked Questions

What is Llama 3.1 405B?

Llama 3.1 405B Instruct is Meta's July 2024 largest open-weight model, scoring 96.9% AI2 RC, 88.6% MMLU, and 73.3% MMLU-Pro with 128K context. It was the first open-weight model to match GPT-4-class MMLU performance.

Is Llama 3.1 405B open source?

The weights are open on Hugging Face under the Llama 3.1 License. Commercial use is permitted with some restrictions.

Should I use Llama 3.1 405B or Llama 4 Maverick?

For new deployments, Llama 4 Maverick is strongly preferred: better benchmark scores, 1M context, multimodal capability, and dramatically lower inference cost (17B active MoE vs 405B dense). Llama 3.1 405B is appropriate for existing integrations or when a dense 405B architecture is specifically required.

--- *Specs from Meta's official Llama 3.1 announcement (July 2024) and Benchgen evaluations. Last updated 2026-07-24.*

Llama 3.1 405B Instruct — Evaluations

Evaluations