FluidStack 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
FluidStack
https://www.fluidstack.io
FluidStack is a cloud GPU infrastructure provider that aggregates underutilized GPU capacity from data centers worldwide to offer on-demand and reserved GPU compute at competitive prices. The platform enables AI companies, researchers, and developers to access large-scale GPU clusters for training and inference workloads, including support for high-performance interconnects like InfiniBand. FluidStack differentiates itself by sourcing capacity from a distributed network of partner data centers, providing cost-effective alternatives to hyperscale cloud providers for AI/ML workloads.
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 | FluidStack | Together AI |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Contact Sales | Free |
| Plans Available | 1 | 6 |
| Features Tracked | 16 | 15 |
| Founded | 2019 | 2022 |
| Headquarters | London, United Kingdom | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| OpenAI-Compatible APIs | ||
| core | ||
| Autoscaling GPU Clusters | ||
| Dedicated GPU Clusters | ||
| Dedicated Model Inference | ||
| Fine-Tuning Workflows | ||
| Full-Stack Observability | ||
| Fully Managed Clusters | ||
| H100/H200/B200/GB200 Support | ||
| High-Performance Inference | ||
| InfiniBand Interconnects | ||
| Instant GPU Clusters | ||
| Kubernetes & Slurm | ||
| Kubernetes Support | ||
| Low-Latency Inference | ||
| NVIDIA GPU Support | ||
| Pay-As-You-Go Pricing | ||
| Rapid Deployment | ||
| Self-Healing Clusters | ||
| Serverless Inference | ||
| Slurm Support | ||
| Transparent Pricing | ||
| Zero Egress Fees | ||
| custom | ||
| Custom Data Centers | ||
| integration | ||
| Distributed Data Access | ||
| Open-Source Model Hub | ||
| SDK Support | ||
| security | ||
| Secure Access Controls | ||
| Single-Tenant Isolation | ||
| support | ||
| 15-Minute Response SLA | ||
| 99% Uptime SLA | ||
| Proactive Monitoring | ||
Pricing
Compare pricing plans and value for money
FluidStack
Contact Sales
Best For
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
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 FluidStack, Together AI is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
FluidStack
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
- Rapid deployment of multi-thousand GPU clusters in as little as 48 hours with zero-setup management.
- Single-tenant isolation at hardware, network, and storage levels eliminates noisy neighbors unlike hyperscalers.
- Supports latest NVIDIA H100/H200/B200/GB200 GPUs with InfiniBand and 99% uptime SLA.
- 24/7 engineering support via Slack with 15-minute response times and proactive monitoring.
- Enterprise-only pricing requires contacting sales, lacking transparent pay-as-you-go rates.
- Small team of 11-50 employees and seed funding may limit scalability versus larger competitors.
- Aggregated capacity from partner data centers could introduce variability in global availability.
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
FluidStack
Together AI
Comparison FAQ
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