Reka Flash 3.1

What the release provides

The release targets coding and adaptation for agent tasks. It uses the cl100k_base tokenizer and its own conversation format. Reka describes it as primarily English and distributes a separate quantized version.Reka Flash 3.1 model card

How to use it well

Practical guidance. Use the supplied conversation template and stopping markers. Review tool behavior after any agent fine-tuning; a coding benchmark does not establish that an agent handles permissions or failures correctly.

Quantized package

This Apache 2.0 release uses Reka Quant to reduce quantization error. The distributed GGUF uses the Q3_K_S format.Reka Flash 3.1 Q3_K_S model card

The package works with llama.cpp-compatible tools. Reka’s quantization method combines calibrated error reduction with online self-distillation. The model retains Flash 3.1’s English focus and conversation format.Reka Flash 3.1 Q3_K_S model card

Practical guidance. Measure memory use with the intended conversation length. Compare accepted answers with the full-precision release on the tasks that matter before choosing the smaller package.