Reka Flash 3 Description
Reka Flash 3 is an AI model with 21 billion parameters developed by Reka AI. It excels in general chat, programming, instruction following and function calling. It can process and reason with text, audio, video, or image inputs. This makes it a general-purpose, compact solution for a variety of applications. Reka Flash 3, which was trained from scratch using diverse datasets including publically accessible and synthetic data for optimization, underwent instruction tuning with curated, high quality data. The final stage of training involved reinforcement learning with REINFORCE Let One Out (RLOO), which included both model-based as well as rule-based rewards. This enhanced its reasoning abilities. Reka Flash 3, with a context length 32,000 tokens is competitive with proprietary models such as OpenAI's O1-mini and is suitable for low-latency deployments or on-device deployments. Full precision of the model requires 39GB (fp16), however, it can be compressed down to 11GB by using 4-bit quantization.
Reka Flash 3 Alternatives
Mistral NeMo
Mistral NeMo, our new best small model. A state-of the-art 12B with 128k context and released under Apache 2.0 license. Mistral NeMo, a 12B-model built in collaboration with NVIDIA, is available. Mistral NeMo has a large context of up to 128k Tokens. Its reasoning, world-knowledge, and coding precision are among the best in its size category. Mistral NeMo, which relies on a standard architecture, is easy to use. It can be used as a replacement for any system that uses Mistral 7B. We have released Apache 2.0 licensed pre-trained checkpoints and instruction-tuned base checkpoints to encourage adoption by researchers and enterprises. Mistral NeMo has been trained with quantization awareness to enable FP8 inferences without performance loss. The model was designed for global applications that are multilingual. It is trained in function calling, and has a large contextual window. It is better than Mistral 7B at following instructions, reasoning and handling multi-turn conversation.
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OpenAI o3-mini
OpenAI o3 Mini is a lightweight version o3 AI model that offers powerful reasoning capabilities, but in a more accessible and efficient package. O3-mini is designed to break complex instructions down into smaller, more manageable steps. It excels at coding tasks, competitive programing, and problem solving in mathematics and sciences. This compact model offers the same high level of precision and logic that its larger counterpart, but with reduced computation requirements. It is ideal for use in resource constrained environments. The o3 mini's deliberative alignment ensures ethical, safe and context-aware decisions. This makes it a versatile tool that can be used by developers, researchers and businesses looking for a balance between performance, efficiency and safety.
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LLaVA
LLaVA is a multimodal model that combines a Vicuna language model with a vision encoder to facilitate comprehensive visual-language understanding. LLaVA's chat capabilities are impressive, emulating multimodal functionality of models such as GPT-4. LLaVA 1.5 has achieved the best performance in 11 benchmarks using publicly available data. It completed training on a single 8A100 node in about one day, beating methods that rely upon billion-scale datasets. The development of LLaVA involved the creation of a multimodal instruction-following dataset, generated using language-only GPT-4. This dataset comprises 158,000 unique language-image instruction-following samples, including conversations, detailed descriptions, and complex reasoning tasks. This data has been crucial in training LLaVA for a wide range of visual and linguistic tasks.
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Reka
Our enterprise-grade multimodal Assistant is designed with privacy, efficiency, and security in mind. Yasa is trained to read text, images and videos. Tabular data will be added in the future. Use it to generate creative tasks, find answers to basic questions or gain insights from your data. With a few simple commands, you can generate, train, compress or deploy your model on-premise. Our proprietary algorithms can be used to customize our model for your data and use case. We use proprietary algorithms for retrieval, fine tuning, self-supervised instructions tuning, and reinforcement to tune our model using your datasets.
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Company Details
Company:
Reka
Year Founded:
2022
Headquarters:
United States
Website:
www.reka.ai/news/introducing-reka-flash
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