Llama vs Together AI

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Llama Fine-tuning	Together AI Fine-tuning
Tagline	Meta's open-weight LLM family covering 1B mobile models up to 405B frontier and natively multimodal 10M-context Llama 4 variants.	Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
Category	Fine-tuning	Fine-tuning
Pricing	Freemium· Weights free under Llama Community License; partner API inference ~$0.19-$0.49 per 1M tokens	Paid· Pay-per-token; fine-tuning per-token
Model	Llama 4 (Maverick, Scout), Llama 3.3/3.2/3.1	Llama / Mistral / Qwen / DeepSeek and others
Editorial score	—	8.6 / 10
Use cases	self-hosted-llmfine-tuningmultimodal-chatsynthetic-dataedge-inferencerag-backbone	open modelsfine-tuninginference
Pros	Open weights from 1B edge models to 405B frontier with permissive commercial license Natively multimodal Llama 4 with up to 10M-token context Runs anywhere: Ollama, vLLM, llama.cpp, Bedrock, Groq, Together Aggressive inference pricing on partner clouds (~$0.19-$0.49/M tokens) Huge fine-tuning ecosystem and community tooling	Wide open-model catalogue Competitive inference pricing Fine-tune + serve in one place Dedicated endpoints for production
Cons	License is source-available, not OSI-approved (700M MAU clause) Tool-use and agentic reasoning still trail GPT-4o and Claude on hardest tasks No polished first-party chat product or hosted playground Largest models require serious GPU budget to self-host	Latency varies by model Less polish than OpenAI
Website	www.llama.com	www.together.ai

Pick Llama if

✅ Open weights from 1B edge models to 405B frontier with permissive commercial license
✅ Natively multimodal Llama 4 with up to 10M-token context
✅ Runs anywhere: Ollama, vLLM, llama.cpp, Bedrock, Groq, Together
✅ Aggressive inference pricing on partner clouds (~$0.19-$0.49/M tokens)

Pick Together AI if