Plano vs Together AI: Inference & Compute Comparison
Compare Plano and Together AI side by side. Both are tools in the Inference & Compute category.
Updated March 10, 2026
The short answer
Choose Plano if fills critical infrastructure gap between frameworks and production.
Choose Together AI if competitive pricing starting at USD 0.10 per million tokens.
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Quick Comparison
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| Category | Inference & Compute | Inference & Compute |
| Pricing | — | Usage-based |
| Best For | — | Developers and companies deploying open-source AI models in production |
| Website | github.com | together.ai |
| Key Features | — |
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| Use Cases | — |
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Pros & Cons: Plano vs Together AI
- +Fills critical infrastructure gap between frameworks and production
- +Built on battle-tested Envoy proxy
- +Language and framework agnostic
- +Strong open-source community (5,800+ GitHub stars)
- +Modular design - use only what you need
- −Relatively new project (2024)
- −Production pricing not transparent
- −Requires infrastructure expertise for self-hosting
- +Competitive pricing starting at USD 0.10 per million tokens
- +50 percent discounts on batch inference and prompt caching
- +Strong backing from NVIDIA and Salesforce Ventures
- +Flexible deployment with both serverless and dedicated options
- −Focused on open-source models may limit access to proprietary models
- −Per-minute billing for dedicated GPUs can be complex to predict
- −Newer platform with less extensive documentation than established providers
- −Pricing varies significantly by model making cost planning difficult
Pricing: Plano vs Together AI
- · Full proxy source code
- · Self-hosted deployment
- · Community support
- · All core features
- · Hosted Plano in US-central
- · Arch LLM family access
- · Development and testing
- · No setup required
- · Production API keys
- · Regional deployment
- · Enterprise support
- · Custom SLAs
- · Pay-as-you-go
- · Multiple open-source models
- · USD 5 free credit
- · Llama 3 70B at USD 0.90/M tokens
- · Bulk processing discount
- · Async execution
- · Cost optimization
- · H100, H200 GPUs
- · Reserved capacity
- · Production workloads
- · Custom pricing
When to Choose Plano vs Together AI
- Hosting open-source LLMs in production
- Fine-tuning models on custom data
- Cost-efficient inference at scale
About Plano
Plano by Katanemo is an open-source AI-native proxy and data plane for agentic applications, providing built-in orchestration, safety, observability, and smart LLM routing. Built on Envoy proxy, Plano centralizes agent orchestration, model management, and observability as modular building blocks that fit cleanly into existing architectures. With over 5,800 GitHub stars, Plano addresses the critical gap between agent frameworks and production infrastructure, handling the complex middle layer that teams previously had to build themselves.
Plano is designed to work with any programming language or AI framework, delivering agents faster to production by handling orchestration, guardrail filters for safety and moderation, rich agentic signals and traces for continuous improvement, and smart LLM routing APIs for model agility. The platform offers developers the flexibility to configure only what they need, from basic proxy functionality to full orchestration and observability, while staying focused on their agent's core logic rather than infrastructure concerns.
Developed by Katanemo, a software development company founded in 2022 and headquartered in Bellevue, Washington, Plano represents a new architectural pattern for agentic applications. The project offers free hosting of Plano and the Arch family of LLMs (including Plano-Orchestrator-4B and Arch-Router) in the US-central region for development, with options to run locally or contact the team for production API keys. This approach allows developers to quickly prototype and test before scaling to production deployments.
About Together AI
Together AI is a cloud-based platform for building with open-source generative AI, founded on June 11, 2022 in San Francisco by Ce Zhang, Chris Re, Percy Liang, and Vipul Ved Prakash. The company raised USD 305 million in Series B funding in 2025 with participation from industry leaders including NVIDIA and Salesforce Ventures. Together AI provides serverless inference with pay-as-you-go pricing starting from USD 0.10 per million tokens for small models and USD 0.90 for Llama 3 70B, with a free USD 5 credit to start. The platform offers a 50 percent discount on batch inference and 50 percent savings on prompt caching for repetitive queries. For teams requiring dedicated resources, Together AI provides GPU endpoints billed per minute, with high-end H100 and H200 GPUs available. The platform specializes in open-source model deployment and provides instant GPU clusters for training and inference workloads. Together AI has become a leading platform for teams building with open-source AI models, offering both serverless convenience and dedicated infrastructure options.
What is Inference & Compute?
Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.
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