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Together AI expands LLM fine-tuning, adds longer contexts

Together AI has enhanced its fine-tuning platform to support a wider array of large language models, including recent releases from DeepSeek, Qwen, and Meta, alongside OpenAI's gpt-oss. The platform now offers expanded context lengths, up to 131k tokens for some models, at no additional cost, facilitating tasks like long-document processing and complex code editing. Separately, Together AI researchers have explored LLM behavior using minimal, topic-neutral prompts to uncover inherent model preferences, finding that GPT-OSS favors programming and math, Llama leans literary, DeepSeek often produces religious content, and Qwen tends toward multiple-choice questions. AI

IMPACT Together AI's platform updates enable developers to fine-tune a broader range of large models with extended context, potentially lowering costs and improving performance on complex tasks.

RANK_REASON This cluster details significant platform updates from an AI company, including expanded model support and new features like extended context lengths, alongside a research paper exploring LLM behavior.

Read on Together AI blog →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Together AI expands LLM fine-tuning, adds longer contexts

COVERAGE [2]

  1. Together AI blog TIER_1 Deutsch(DE) ·

    Fine

    Together AI expands Fine-Tuning Platform: train 100B+ models, extend context lengths, integrate with Hugging Face Hub, and access new DPO options.

  2. Together AI blog TIER_1 English(EN) ·

    What do LLMs think when you don't tell them what to think about?

    What do language models generate when you don't tell them what to generate? New research reveals that LLM families have distinct 'knowledge priors'—GPT models default to code and math, Llama favors narratives, DeepSeek generates religious content, and Qwen outputs exam questions.