// COMPARISON

RetNet

A head-to-head benchmark comparison of RetNet across 0 evaluations.

The models

Language Proprietary
Params
6.7B
Context
β€”
Released
Jul 2023

In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-c.

Full RetNet specs β†’

Benchmark comparison

No shared benchmark scores found for these models yet.

Frequently asked questions

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This comparison covers 0 benchmarks on which at least one of the selected models has a published score.

Where do the benchmark scores come from? β–Ά

Scores are aggregated from official model cards, technical reports and standard public evaluations, and link back to each benchmark's source. They are updated as new results are published.

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