CoreWeave vs Together AI: Inference & Compute Comparison
Compare CoreWeave and Together AI side by side. Both are tools in the Inference & Compute category.
Updated March 9, 2026
The short answer
Choose CoreWeave if significantly lower GPU pricing compared to AWS, Azure, and GCP hyperscalers.
Choose Together AI if competitive pricing starting at USD 0.10 per million tokens.
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Quick Comparison
| Category | Inference & Compute | Inference & Compute |
| Pricing | Usage-based | Usage-based |
| Best For | AI companies and startups that need large-scale GPU clusters for training and inference | Developers and companies deploying open-source AI models in production |
| Website | coreweave.com | together.ai |
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Pros & Cons: CoreWeave vs Together AI
- +Significantly lower GPU pricing compared to AWS, Azure, and GCP hyperscalers
- +Purpose-built for AI workloads with optimized networking and Kubernetes orchestration
- +Transparent pricing with no hidden fees for data egress or core services
- +Up to 60% discounts available for committed usage, excellent for predictable workloads
- −No free tier or trial period, requiring upfront payment commitment
- −Smaller ecosystem compared to major cloud providers may limit integration options
- −Less mature than hyperscalers in terms of managed services and tooling
- −À la carte pricing model requires careful calculation of total costs including CPU and RAM
- +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: CoreWeave vs Together AI
- · Pay-as-you-go pricing
- · Immediate availability
- · No commitments
- · Free data egress
- · Up to 60% discount
- · Reserved capacity
- · Predictable pricing
- · Priority support
- · 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 CoreWeave vs Together AI
- Large language model training
- Distributed training across GPU clusters
- High-performance inference at scale
- Hosting open-source LLMs in production
- Fine-tuning models on custom data
- Cost-efficient inference at scale
About CoreWeave
CoreWeave is a specialized cloud infrastructure provider founded in 2017 in New Jersey by Michael Intrator, Brian Venturo, Brannin McBee, and Peter Salanki. Originally started by three commodities traders, CoreWeave has grown into a leading GPU cloud platform built specifically for AI and machine learning workloads. Based in Livingston, New Jersey, with approximately 1,871 employees as of January 2026, CoreWeave offers on-demand access to NVIDIA H100 and A100 GPUs with significantly lower pricing than traditional hyperscalers. The platform provides Kubernetes-native orchestration, fast networking, and flexible scaling, making it popular with AI labs, research institutions, and startups that need large GPU clusters without long-term commitments. CoreWeave's infrastructure is designed from the ground up for GPU-accelerated workloads, offering up to 60% discounts over on-demand prices for committed usage, with transparent pricing that doesn't charge for data egress, IOPS, or core networking services.
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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