# Reflection AI releases Beam weights and recipes

> Reflection AI open-sources Beam weights and post-training recipes for developers.
- Title: Reflection AI releases Beam weights and recipes · SiliconANGLE
- Summary: Reflection AI open-sources Beam weights and post-training recipes for developers. Reflection AI made Beam's weights and training recipes available on Hugging…
- Keywords: reflection ai, beam, hugging face, large language model, post-training recipes, quantization, speculative decoding, serving engine, technology, enterprise, Reflection, releases
- Source: SiliconANGLE — https://siliconangle.com/2026/10/16/reflection-ai-open-sources-beams-weights-post-training-recipes
- Author: Maria Deutscher
- Published: 2026-10-16T22:52:38+00:00
- Read time: 1 min
- Topics: reflection ai, beam, hugging face, large language model, post-training recipes, quantization, speculative decoding, serving engine, technology, enterprise
## Reflection AI opens Beam weights
Reflection AI made Beam's weights available on Hugging Face for developers to use.
## Beam features 500 billion parameters
Beam has about 500 billion parameters but performs better than four times its size on some benchmarks.
## Beam uses less computing power
Beam uses significantly less computing power and memory than larger models.
## Reflection AI trained Beam for two months
Reflection AI trained Beam over two months using several thousand high-end graphics cards.
## Error mitigation for Beam
Reflection AI developed custom reliability optimization algorithms to avoid training-inference mismatches.
## Beam quantization variants
Beam offers scaled-down variants that keep information in smaller data units through quantization.
## Beam training recipes released
Reflection AI released training recipes and code templates for developers to fine-tune Beam.
## Key takeaway

Reflection AI made Beam's weights and training recipes available on Hugging Face to let developers customize its large language model.