title: Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language
    Models
summary: We introduce Reka Core, Flash, and Edge, a series of powerful multimodal
  language models trained from scratch by Reka. Reka models are able to process
  and reason with text, images, video, and audio inputs. This technical report
  discusses details of training some of these models and provides comprehensive
  evaluation results. We show that Reka Edge and Reka Flash are not only
  state-of-the-art but also outperform many much larger models, delivering
  outsized values for their respective compute class. Meanwhile, our most capable
  and largest model, Reka Core, approaches the best frontier models on both
  automatic evaluations and blind human evaluations. On image question answering
  benchmarks (e.g. MMMU, VQAv2), Core performs competitively to GPT4-V.
  Meanwhile, on multimodal chat, Core ranks as the second most preferred model
  under a blind third-party human evaluation setup, outperforming other models
  such as Claude 3 Opus. On text benchmarks, Core not only performs competitively
  to other frontier models on a set of well-established benchmarks (e.g. MMLU,
  GSM8K) but also outperforms GPT4-0613 on human evaluation. On video question
  answering (Perception-Test), Core outperforms Gemini Ultra. Models are shipped
  in production at http://chat.reka.ai . A showcase of non cherry picked
  qualitative examples can also be found at http://showcase.reka.ai .
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paper_title: Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language
    Models
paper_summary: We introduce Reka Core, Flash, and Edge, a series of powerful multimodal
  language models trained from scratch by Reka. Reka models are able to process
  and reason with text, images, video, and audio inputs. This technical report
  discusses details of training some of these models and provides comprehensive
  evaluation results. We show that Reka Edge and Reka Flash are not only
  state-of-the-art but also outperform many much larger models, delivering
  outsized values for their respective compute class. Meanwhile, our most capable
  and largest model, Reka Core, approaches the best frontier models on both
  automatic evaluations and blind human evaluations. On image question answering
  benchmarks (e.g. MMMU, VQAv2), Core performs competitively to GPT4-V.
  Meanwhile, on multimodal chat, Core ranks as the second most preferred model
  under a blind third-party human evaluation setup, outperforming other models
  such as Claude 3 Opus. On text benchmarks, Core not only performs competitively
  to other frontier models on a set of well-established benchmarks (e.g. MMLU,
  GSM8K) but also outperforms GPT4-0613 on human evaluation. On video question
  answering (Perception-Test), Core outperforms Gemini Ultra. Models are shipped
  in production at http://chat.reka.ai . A showcase of non cherry picked
  qualitative examples can also be found at http://showcase.reka.ai .
paper_ai_keywords: multimodal language models text images video audio inputs Reka Edge Reka Flash Reka Core state-of-the-art compute class automatic evaluations blind human evaluations image question answering MMMU VQAv2 GPT4-V multimodal chat Claude 3 Opus MMLU GSM8K GPT4-0613 video question answering Perception-Test Gemini Ultra