EAGLE LLaMA3 Instruct 8B

Llama 3

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 20242K context≈ 1,536 words8B params

A lean, fast-talking assistant built around speculative decoding — it drafts multiple tokens ahead and self-corrects, making it noticeably quicker in inference pipelines than standard autoregressive models of similar size. It inherits LLaMA 3's instruction-following habits, so responses are structured and reasonably precise, but the EAGLE layer adds complexity that can surface subtle inconsistencies if the draft head misfires.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Reasoning & Logic

EAGLE LLaMA3 Instruct 8B

Llama 3

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 20242K context≈ 1,536 words8B params

A lean, fast-talking assistant built around speculative decoding — it drafts multiple tokens ahead and self-corrects, making it noticeably quicker in inference pipelines than standard autoregressive models of similar size. It inherits LLaMA 3's instruction-following habits, so responses are structured and reasonably precise, but the EAGLE layer adds complexity that can surface subtle inconsistencies if the draft head misfires.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Moderate

Reasoning & Logic

Glossary

AutoregressiveA model that generates text one token at a time by predicting the next word based on all previous words in the sequence.Autoregressive ModelsLanguage models that generate text one token (word piece) at a time, where each new token depends on all previously generated tokens.DecodingConverting model outputs into human-readable text or structured predictions.Draft HeadThe smaller neural network component in speculative decoding that quickly generates candidate tokens before verification by the main model.InferenceThe process of running a trained model to generate predictions or outputs from new inputs.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.Speculative DecodingA technique where a smaller model quickly drafts multiple token predictions ahead of time, which a larger model then verifies, reducing the total time needed to generate text.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Use Case Fit

Glossary