Meta Llama 3 8B Instruct
Meta AI's Meta Llama 3 8B Instruct is a chat model optimized for dialogue use cases, with capabilities including function calling, JSON mode, reasoning, streaming, and text generation. It is genuinely best at generating helpful and safe text outputs, thanks to its supervised fine-tuning and reinforcement learning with human feedback training.
Input
Output
Context
8K
Max Output
8K
Parameters
8B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Benchmarks
Resources & Links
Estimated GPU requirements for Meta Llama 3 8B Instruct
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Meta Llama 3 8B Instruct
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Meta Llama 3 8B Instruct advertises a context window of 8,192 tokens, with a maximum output of 8,192 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Meta Llama 3 8B Instruct is an open-weight model released under the Llama3 license, so the weights can be downloaded and self-hosted within that license's terms.
Meta Llama 3 8B Instruct accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
Meta Llama 3 8B Instruct has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Meta Llama 3 8B Instruct is shown as not available rather than estimated.
Not on the managed pool today; Meta Llama 3 8B Instruct is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 8.2 GB at INT8 for the weights and a default context, from the catalog's 8B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Sep 13, 2026
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