Llama 3.1 70B
Llama 3.1 70B — Meta large language model (2024) with a 128K-token context window and an MMLU score of 86.0%, released with open weights.
Key specifications
| MMLU (capability) | 86.0% |
|---|---|
| Context window (K tokens) | 128 |
| Input price ($/1M) | 0 |
| Output price ($/1M) | 0 |
About Llama 3.1 70B
The Llama 3.1 70B is a large language model from Meta with a 128K-token context window and an MMLU score of 86.0%. It is open weights, so it can be self-hosted. MMLU measures general knowledge and reasoning; real-world quality also depends on coding, tool use, latency and safety.
The comparisons below show how Llama 3.1 70B stacks up against the alternatives people most often weigh against it, with the specific numbers laid out side by side.
Frequently asked questions
Is the Llama 3.1 70B any good?
Llama 3.1 70B — Meta large language model (2024) with a 128K-token context window and an MMLU score of 86.0%, released with open weights.
What are the key specs of the Llama 3.1 70B?
See the specification table above for the full breakdown.