Agno vs Together AI

A side-by-side comparison of capabilities, autonomy, integrations, and pricing to help you choose.

Short answer: choose Agno if you want high-performance python framework for multi-agent systems (Supervised agent, freemium); choose Together AI if you want cloud for running, fine-tuning, and serving open-source ai models (Assistant, usage).

AgnoTogether AI
What it isHigh-performance Python framework for multi-agent systemsCloud for running, fine-tuning, and serving open-source AI models
Typeframeworkplatform
AutonomySupervised agentAssistant
Pricingfreemiumusage · Per-token usage from ~$0.03 / 1M input tokens; GPU clusters from ~$3.29/hr reserved
Best fordevelopers, smb, enterprisedevelopers, enterprise, mid-market
Deploymentself-hosted, apiapi, saas, on-prem
Modalitiestext, code, api, imagetext, code, image, video, voice, api
Modelsmodel-agnostic, open-sourcellama, open-source, model-agnostic
Protocolsfunction-calling, mcp, rest-apifunction-calling, rest-api
IntegrationsOpenAI, Anthropic, Google, Ollama, pgvector, QdrantOpenAI SDK, LangChain, LlamaIndex, Vercel AI SDK, Hugging Face
Capabilities4 documented6 documented

Agno

  • +Strong performance focus (fast instantiation, low memory) with a clean Python API
  • +Clear path from prototype to production via the AgentOS runtime
  • +Broad model, vector-DB, and tool coverage, all self-hostable
  • -Python-only
  • -Younger and smaller ecosystem than LangChain
Full Agno profile

Together AI

  • +Large catalog of open models across text, image, audio, and video
  • +OpenAI-compatible API makes migration nearly drop-in
  • +Full ladder from serverless to dedicated endpoints to raw GPU clusters
  • -Serves open and bring-your-own models; no proprietary frontier model of its own
  • -It is an inference and compute layer, not an end-to-end agent: orchestration is on you
Full Together AI profile

Which should you choose?

Agno is high-performance python framework for multi-agent systems, best for developers, smb, enterprise. Together AI is cloud for running, fine-tuning, and serving open-source ai models, best for developers, enterprise, mid-market. The right choice depends on the autonomy level you want, your existing integrations, and your budget, all compared above.