Perplexity vs Together AI: Token Pricing, Speed & Intelligence
Full comparison of Perplexity and Together AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Perplexity
Sonar — search-augmented LLMs with real-time web grounding
Perplexity's Sonar models are designed for search-augmented generation, combining LLM reasoning with real-time web retrieval. Unlike standard LLMs, Sonar responses include citations and are grounded in current web content. Ideal for research assistants, news summarisation, and fact-checking applications.
Together AI
Open-source model hosting with competitive inference pricing
Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.
Key metrics
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Live token pricing
Strengths & weaknesses
Perplexity
Together AI
Key differentiators
Every Sonar response includes real-time web citations — the only LLM API purpose-built for grounded, verifiable answers.
The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.
Frequently asked questions
Perplexity FAQs
What is Perplexity Sonar?
Sonar is Perplexity's family of search-augmented LLMs. Unlike standard LLMs, Sonar automatically searches the web and includes citations in every response. Sonar is available in standard and Pro (deep research) variants.
How much does Perplexity API cost?
Perplexity charges per 1M tokens plus a per-request fee for search operations. Check their pricing page for current rates as they vary by model and search depth.
When should I use Perplexity instead of GPT-4o?
Use Perplexity when your application needs real-time, verifiable information with citations — research tools, news summarisation, fact-checking, or any use case where accuracy on current events matters. For creative tasks, coding, or reasoning without web grounding, GPT-4o or Claude are better choices.
Together AI FAQs
What models does Together AI support?
Together AI hosts 100+ open-weight models including the full Llama 3.x family (8B, 70B, 405B), Mixtral, DeepSeek R1, Qwen, and many others. They also support custom fine-tuned model deployment.
How much does Together AI cost?
Llama 3.3 70B costs $0.88/1M tokens (input and output). Llama 3.1 405B is $3.50/1M tokens. Smaller models like Llama 3.2 11B Vision start at $0.18/1M tokens.
Does Together AI support fine-tuning?
Yes. Together AI offers supervised fine-tuning for Llama and other open-weight models. You can upload training data, run fine-tuning jobs, and deploy the resulting model via their inference API.
Provider resources
Perplexity — Sonar — search-augmented LLMs with real-time web grounding
Perplexity's Sonar models are designed for search-augmented generation, combining LLM reasoning with real-time web retrieval. Unlike standard LLMs, Sonar responses include citations and are grounded in current web content. Ideal for research assistants, news summarisation, and fact-checking applications.
Every Sonar response includes real-time web citations — the only LLM API purpose-built for grounded, verifiable answers.
Together AI — Open-source model hosting with competitive inference pricing
Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.
The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.
Key strengths compared
Perplexity
- ▸Real-time web search with automatic citations
- ▸Sonar Pro for deep research with multi-step retrieval
- ▸Grounded responses reduce hallucination on factual queries
Together AI
- ▸Largest selection of open-weight models
- ▸Fine-tuning support for custom model training
- ▸OpenAI-compatible API — easy migration
Provider category context
Perplexity is a inference api, founded in 2022. Together AI is a inference api, founded in 2022. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Perplexity and Together AI host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.