Best Large Language Models for TESS AI
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Compare the Top Large Language Models that integrate with TESS AI as of June 2026
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This a list of Large Language Models that integrate with TESS AI. Use the filters on the left to add additional filters for products that have integrations with TESS AI. View the products that work with TESS AI in the table below.
What are Large Language Models for TESS AI?
Large language models are artificial neural networks used to process and understand natural language. Commonly trained on large datasets, they can be used for a variety of tasks such as text generation, text classification, question answering, and machine translation. Over time, these models have continued to improve, allowing for better accuracy and greater performance on a variety of tasks. Compare and read user reviews of the best Large Language Models for TESS AI currently available using the table below. This list is updated regularly.
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1
ChatGPT
OpenAI
ChatGPT is an AI-powered assistant designed to help users get answers, generate ideas, and complete tasks more efficiently. It supports a wide range of activities, including writing, brainstorming, coding, and research. Users can interact with ChatGPT through text or voice, making it flexible for different use cases. The platform can summarize information, analyze data, and provide insights to improve productivity. It also assists with creative tasks such as content creation, planning, and problem-solving. ChatGPT includes workspace agents that can automate workflows, handle repetitive tasks, and operate across tools. These agents can run tasks independently, such as generating reports or managing processes on a schedule. Overall, ChatGPT serves as a versatile tool for both personal and professional use.Starting Price: Free -
2
ByteDance Seed
ByteDance
Seed Diffusion Preview is a large-scale, code-focused language model that uses discrete-state diffusion to generate code non-sequentially, achieving dramatically faster inference without sacrificing quality by decoupling generation from the token-by-token bottleneck of autoregressive models. It combines a two-stage curriculum, mask-based corruption followed by edit-based augmentation, to robustly train a standard dense Transformer, striking a balance between speed and accuracy and avoiding shortcuts like carry-over unmasking to preserve principled density estimation. The model delivers an inference speed of 2,146 tokens/sec on H20 GPUs, outperforming contemporary diffusion baselines while matching or exceeding their accuracy on standard code benchmarks, including editing tasks, thereby establishing a new speed-quality Pareto frontier and demonstrating discrete diffusion’s practical viability for real-world code generation.Starting Price: Free -
3
Llama 2
Meta
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.Starting Price: Free
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