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 .

翻译：我们推出由Reka从头训练的Reka Core、Flash和Edge系列多模态语言模型。Reka模型能够处理并推理文本、图像、视频及音频输入。本技术报告详细阐述了部分模型的训练过程，并提供了全面的评估结果。研究表明，Reka Edge和Reka Flash不仅达到了业界领先水平，且在各自计算类别中表现出超越许多更大模型的卓越性能。与此同时，我们最强大、规模最大的模型Reka Core在自动评估和盲审人工评估中均逼近最优前沿模型。在图像问答基准测试（如MMMU、VQAv2）中，Core的性能与GPT4-V相当。在多模态对话场景下，Core在第三方盲审人工评估中位列第二受欢迎模型，超越Claude 3 Opus等其他模型。在文本基准测试中，Core不仅在多个成熟基准（如MMLU、GSM8K）上与前沿模型表现相当，更在人工评估中优于GPT4-0613。在视频问答任务（Perception-Test）中，Core的表现超越Gemini Ultra。模型已部署于生产环境，访问地址为http://chat.reaka.ai。非精选定性示例展示可参见http://showcase.reaka.ai。