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Chat-optimized LLM leveraging public datasets and 1M+ human annotations.
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Chat-optimized LLM leveraging public datasets and 1M+ human annotations.
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Auto-regressive LLM with optimized transformers, SFT, and RLHF for alignment with helpfulness and safety preferences.
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Auto-regressive LLM with optimized transformers, SFT, and RLHF for alignment with helpfulness and safety preferences.
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Auto-regressive LLM with optimized transformers, SFT, and RLHF for alignment with helpfulness and safety preferences.
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Auto-regressive LLM with optimized transformers, SFT, and RLHF for alignment with helpfulness and safety preferences.
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Experimental merge of MythoLogic-L2 and Huginn using tensor intermingling for enhanced front and end tensor integration.
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Experimental merge of MythoLogic-L2 and Huginn using tensor intermingling for enhanced front and end tensor integration.
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Instruct Thai large language model with 8 billion parameters based on Llama3.1-8B.
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Instruct Thai large language model with 70 billion parameters, based on Llama3.1-70B.
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Transformer-based decoder-only LLM, pretrained on extensive data, offering improvements over the previous Qwen model.
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Flagship Nous Research MoE model trained on 1M+ GPT-4 and high-quality open dataset entries, excelling across diverse tasks.
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Multilingual LLM pre-trained and instruction-tuned, surpassing open and closed models on key benchmarks.
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Improved instruct fine-tuned version of Mistral-7B-Instruct-v0.1.
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Instruction-tuned 7.61B Qwen2.5 causal LLM with 131K context, RoPE, SwiGLU, RMSNorm, and advanced attention mechanisms.
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Lightweight, SOTA open models from Google, leveraging research and tech behind the Gemini models.
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2B instruct Gemma model by Google: lightweight, open, text-to-text LLM for QA, summarization, reasoning, and resource-efficient deployment.
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Multimodal LLM optimized for visual recognition, image reasoning, captioning, and answering image-related questions.
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MoE LLM trained from scratch and specialized in few-turn interactions for enhanced performance.
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Lightweight Gemma 3 model with 128K context, vision-language input, and multilingual support for on-device AI.
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Lightweight Gemma 3 model (1B) with 128K context, vision-language input, and multilingual support for on-device AI.
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Most lightweight Gemma 3 model, with 128K context, vision-language input, and multilingual support for on-device AI.
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Small Qwen 1.5B distilled with reasoning capabilities from Deepseek R1. Beats GPT-4o on MATH-500 whilst being a fraction of the size.
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Qwen 14B distilled with reasoning capabilities from Deepseek R1. Outperforms GPT-4o in math & matches o1-mini on coding.
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Llama 70B distilled with reasoning capabilities from Deepseek R1. Surpasses GPT-4o with 94.5% on MATH-500 & matches o1-mini on coding.
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Multilingual LLM pre-trained and instruction-tuned, surpassing open and closed models on key benchmarks.
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Lightweight, SOTA open models from Google, leveraging research and tech behind the Gemini models.
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Multilingual LLM pre-trained and instruction-tuned, surpassing open and closed models on key benchmarks.
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70B multilingual LLM, pretrained and instruction-tuned, excels in dialogue use cases, surpassing open and closed models.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Custom NVIDIA LLM optimized to enhance the helpfulness and relevance of generated responses to user queries.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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24B model rivaling GPT-4o mini, and larger models like Llama 3.3 70B. Ideal for chat use cases like customer support, translation and summarization.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Qwen series reasoning model excelling in complex tasks, outperforming conventional instruction-tuned models on hard problems.
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Mixture-of-Experts model challenging top AI models at much lower cost. Updated on March 24th, 2025.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Vision-language model with advanced visual reasoning, video understanding, structured outputs, and agentic capabilities.
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Free endpoint to try this 70B multilingual LLM optimized for dialogue, excelling in benchmarks and surpassing many chat models.
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Lightweight model with vision-language input, multilingual support, visual reasoning, and top-tier performance per size.
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Free endpoint to experiment the power of reasoning models. This distilled model beats GPT-4o on math & matches o1-mini on coding.
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Open-source reasoning model rivaling OpenAI-o1, excelling in math, code, reasoning, and cost efficiency.
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SOTA 109B model with 17B active params & large context, excelling at multi-document analysis, codebase reasoning, and personalized tasks.
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SOTA 128-expert MoE powerhouse for multilingual image/text understanding, creative writing, and enterprise-scale applications.
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12 billion parameter rectified flow transformer capable of generating images from text descriptions.
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Fastest available endpoint for the SOTA open-source image generation model by Black Forest Labs.
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Adapter for FLUX.1 models enabling image variation, refining input images, and integrating into advanced restyling workflows.
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12 billion parameter rectified flow transformer capable of generating an image based on a text description while following the structure of a given input image.
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12 billion parameter rectified flow transformer capable of generating an image based on a text description while following the structure of a given input image.
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12 billion parameter rectified flow transformer capable of generating images from text descriptions.
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Advanced image generation model with FLUX.1-dev architecture, offering high-quality outputs for artistic and commercial use.
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Free endpoint for the SOTA open-source image generation model by Black Forest Labs.
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Multimodal LLM optimized for visual recognition, image reasoning, captioning, and answering image-related questions.
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Multimodal LLM optimized for visual recognition, image reasoning, captioning, and answering image-related questions.
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Lightweight Gemma 3 model with 128K context, vision-language input, and multilingual support for on-device AI.
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Lightweight Gemma 3 model (1B) with 128K context, vision-language input, and multilingual support for on-device AI.
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Most lightweight Gemma 3 model, with 128K context, vision-language input, and multilingual support for on-device AI.
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OSS vision model merging advanced vision with instruction-tuned language understanding for visual reasoning.
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Free endpoint to test this auto-regressive language model that uses an optimized transformer architecture.
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Vision-language model with advanced visual reasoning, video understanding, structured outputs, and agentic capabilities.
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Lightweight model with vision-language input, multilingual support, visual reasoning, and top-tier performance per size.
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SOTA 109B model with 17B active params & large context, excelling at multi-document analysis, codebase reasoning, and personalized tasks.
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SOTA 128-expert MoE powerhouse for multilingual image/text understanding, creative writing, and enterprise-scale applications.
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Low-latency, ultra-realistic voice model, served in partnership with Cartesia.
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LLM trained on 2T tokens with double Llama 1's context length, available in 7B, 13B, and 70B parameter sizes.
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8B Llama 3.1 model fine-tuned for content safety, moderating prompts and responses in 8 languages with MLCommons alignment.
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11B Llama 3.2 model fine-tuned for content safety, detecting harmful multimodal prompts and text in image reasoning use cases.
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8B Llama 3-based safeguard model for classifying LLM inputs and outputs, detecting unsafe content and policy violations.
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7B Llama 2-based safeguard model for classifying LLM inputs and outputs, detecting unsafe content and policy violations.
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7.3B model surpassing Llama 2 13B, nearing CodeLlama 7B on code, with GQA for speed and SWA for efficient long-sequence handling.
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Lightweight Gemma 3 model with 128K context, vision-language input, and multilingual support for on-device AI.
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Lightweight Gemma 3 model (1B) with 128K context, vision-language input, and multilingual support for on-device AI.
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Most lightweight Gemma 3 model, with 128K context, vision-language input, and multilingual support for on-device AI.
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SOTA code LLM with advanced code generation, reasoning, fixing, and support for up to 128K tokens.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Best-in-class open-source LLM trained with IDA for alignment, reasoning, and self-reflective, agentic applications.
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Lightweight model with vision-language input, multilingual support, visual reasoning, and top-tier performance per size.
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80M checkpoint of M2-BERT, pretrained with sequence length 32768, and it has been fine-tuned for long-context retrieval.
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This model maps any text to a low-dimensional dense vector using FlagEmbedding.
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80M checkpoint of M2-BERT, pretrained with sequence length 8192, and it has been fine-tuned for long-context retrieval.
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80M checkpoint of M2-BERT, pretrained with sequence length 2048, and it has been fine-tuned for long-context retrieval.
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Universal English sentence embedding model by WhereIsAI with 1024-dim embeddings and 512 context length support.
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BAAI v1.5 large maps text to dense vectors for retrieval, classification, clustering, semantic search, and LLM databases.
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Salesforce Research's proprietary fine-tuned rerank model with 8K context, outperforming Cohere Rerank for superior document retrieval.
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AiTradeStore team believes that openness and transparency in AI will foster innovation and lead to the most beneficial outcomes for society.
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