Heroku vs Together AI Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
Heroku
https://www.heroku.com
Heroku is a cloud platform as a service (PaaS) that enables companies to build, deliver, monitor and scale applications. The platform supports several programming languages and allows developers to deploy, manage, and scale modern apps without having to manage the underlying infrastructure. Heroku was acquired by Salesforce in 2010 and has since become one of the most popular PaaS solutions for web application deployment.
Together AI
https://www.together.ai
Together AI is a cloud platform that enables developers and enterprises to run, fine-tune, and deploy open-source large language models (LLMs) at scale with high performance and cost efficiency. The platform provides access to a wide range of open-source models including LLaMA, Mistral, and others through a unified API, along with tools for custom model fine-tuning and inference optimization. Together AI also conducts AI research and has developed its own inference infrastructure designed to deliver fast and affordable generative AI capabilities.
Quick Comparison
| Detail | Heroku | Together AI |
|---|---|---|
| Category | Platform as a Service (PaaS) | AI Cloud Infrastructure |
| Starting Price | Contact Sales | Free |
| Plans Available | 0 | 6 |
| Features Tracked | 17 | 15 |
| Founded | 2007 | 2022 |
| Headquarters | San Francisco, USA | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| CLI Access | ||
| OpenAI-Compatible APIs | ||
| core | ||
| Application Metrics | ||
| Autoscaling | ||
| Autoscaling GPU Clusters | ||
| Dedicated Model Inference | ||
| Dynos | ||
| Fine-Tuning Workflows | ||
| Full-Stack Observability | ||
| Heroku Dashboard | ||
| Heroku Key-Value Store | ||
| Heroku Pipelines | ||
| Heroku Postgres | ||
| High-Performance Inference | ||
| Instant GPU Clusters | ||
| Kubernetes & Slurm | ||
| Managed Inference and Agents | ||
| Multi-language Support | ||
| NVIDIA GPU Support | ||
| Pay-As-You-Go Pricing | ||
| Self-Healing Clusters | ||
| Serverless Inference | ||
| Zero Egress Fees | ||
| custom | ||
| Buildpacks | ||
| integration | ||
| Add-ons Marketplace | ||
| Apache Kafka on Heroku | ||
| Heroku AppLink | Add-on | |
| Model Context Protocol (MCP) | ||
| Open-Source Model Hub | ||
| SDK Support | ||
| security | ||
| Security Patches | ||
| support | ||
| Team Collaboration | ||
Pricing
Compare pricing plans and value for money
Heroku
Contact Sales
No pricing data available yet
Best For
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
Together AI
From $0/mo
Price Components
- GLM-5.1 Input Tokens: $1.4/1M tokens
- GLM-5.1 Output Tokens: $4.4/1M tokens
- Llama 3.3 70B: $0.88/1M tokens
- 1x H100 80GB: $3.99/hour
- 1x H200 141GB: $5.49/hour
Best For
Developers and enterprises needing fast, cost-efficient deployment and fine-tuning of open-source LLMs with flexible GPU clusters and serverless APIs.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Heroku, Together AI is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
Heroku
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
- Git push deployment and dyno autoscaling enable instant scaling for web apps, unlike more complex setups on AWS or Azure.
- Managed data services like Heroku Postgres and Redis handle backups and HA, freeing developers from infra tasks.
- Native buildpacks for Node.js, Python, Java, and others simplify multi-language deploys versus custom configs elsewhere.
- Doubled 1GB slug limit supports AI/ML frameworks, boosting complex app compatibility.
- Transitioning to sustaining engineering mode limits new features, lagging behind innovative PaaS like Upsun.
- Runs atop AWS EC2 with dyno-based pricing that can escalate costs for high-traffic apps versus granular cloud options.
- Enterprise feature freeze pushes users toward Salesforce alternatives like Agentforce.
Together AI
Developers and enterprises needing fast, cost-efficient deployment and fine-tuning of open-source LLMs with flexible GPU clusters and serverless APIs.
- Serverless inference with OpenAI-compatible APIs and up to 4x faster performance via custom optimizations differentiates from generic cloud providers.
- Instant self-service GPU clusters up to 64 NVIDIA H100/H200 GPUs deploy in minutes with zero egress fees and autoscaling.
- Fine-tuning for 200+ open-source models like LLaMA and Mistral using proprietary data, with dedicated $2,872/month inference options.
- Full-stack observability via Grafana dashboards and pay-as-you-go token-based pricing for cost-efficient scaling.
- Young company founded in 2022 with 51-200 employees may lack the enterprise maturity and global scale of hyperscalers like AWS.
- Focus on open-source models limits access to proprietary LLMs from providers like OpenAI or Anthropic.
- High entry for dedicated options at $2,872/month suits enterprises but may deter small teams preferring fully serverless.
Company Info
Company details and background
Heroku
Together AI
Comparison FAQ
Common questions about comparing Heroku and Together AI
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