Meta

MLlama 3.1 70B InstructOPEN

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors.

Context window
131K
tokens
Input price
$0.4
per M tokens
Output price
$0.4
per M tokens
Provider
Meta

Prices update automatically — checked hourly against provider list prices.

See model comparisons → Compare all model prices

Benchmarks & performance

Independent benchmark scores for Llama 3.1 70B Instruct, measured by Artificial Analysis. Higher is better.

Intelligence index6.8
Math index4
GPQA40.9%
MMLU-Pro67.6%
Humanity's Last Exam4.6%
Long Context Reasoning6.3%
LiveCodeBench23.2%
SciCode26.7%
MATH-50064.9%
AIME17.3%
AIME 20254%
IFBench34.4%
τ²-Bench15.2%
Terminal-Bench Hard3%
💰 Blended price$0.56 / 1M tokens
📈 Value12.1 intelligence points per $
vs. models measured heretop 92%
Scores higher than 8% of the 239 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.24 per 1M tokens (median of 21) — this one costs $0.4.
Cheaper and better on this index: MiniMax M3 (batch) · Hy3 · DeepSeek V4 Flash and 56 more
Benchmark data by Artificial Analysis

About this model

Llama 3.1 70B Instruct is an open-weight AI model by Meta. You can download and self-host it for free; the prices below are hosted-API list prices, tracked hourly, for when you prefer convenience over self-hosting.

Frequently asked questions

What is Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct is an AI language model from Meta. It is open-weight: you can download it and run it on your own hardware, for free. It scores 6.8 on the Artificial Analysis intelligence index.

Is Llama 3.1 70B Instruct free?

The weights are free and open — you can self-host Llama 3.1 70B Instruct and pay nothing per token. If you prefer a hosted API, list prices are $0.4 per million input tokens and $0.4 per million output tokens.

What is Llama 3.1 70B Instruct good at?

Independent benchmarks from Artificial Analysis give it GPQA 40.9%, MMLU-Pro 67.6%, Humanity's Last Exam 4.6%, Long Context Reasoning 6.3%, LiveCodeBench 23.2%, SciCode 26.7%, MATH-500 64.9%, AIME 17.3%, AIME 2025 4%, IFBench 34.4%, τ²-Bench 15.2%, Terminal-Bench Hard 3%. It is particularly used for mathematical reasoning.

Can I self-host Llama 3.1 70B Instruct?

Yes. Llama 3.1 70B Instruct has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.

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