Baseten vs Together AI Pricing (2026)
How do these two stack up on price? Here's what each one costs, what you get, and where the value sits.
| Baseten | Together AI | |
|---|---|---|
| Starts at | Custom | Custom |
| Number of plans | 3 | 7 |
| Free plan | — | |
| Free trial | — | |
| Pricing model | usage-based | usage-based |
Basic
- Dedicated deployments
- Model APIs
- Training
- Fast cold starts
- SOC 2 Type II and HIPAA compliant
- Email and in-app chat support
Pro
- Priority access to high-demand GPUs
- Dedicated compute
- Higher Model API rate limits
- Hands-on engineering expertise
- Dedicated support on Slack and Zoom
Enterprise
- Custom SLAs
- Self-host deployments
- On-demand flex compute
- Use existing cloud commitments
- Full control over data residency
- Advanced security and compliance
- Custom global regions
- Advanced RBAC with Teams
Serverless Inference
- Chat models (price per 1M tokens)
- Vision models (price per 1M tokens)
- Image generation models (price per image or per mp)
- Audio / TTS models (price per 1M characters)
- Video generation models (price per video)
- Transcription models (price per audio minute)
- Embeddings models (price per 1M tokens)
- Moderation models (price per 1M tokens)
- Batch API pricing available
Provisioned Throughput
- Reserved dedicated capacity in throughput units (PTUs)
- Fixed capacity per PTU with model-dependent tokens-per-minute
- MiniMax M3 support
- GLM-5.2 support
Dedicated Inference
- Guaranteed performance (no sharing)
- Support for custom models
- Autoscaling & traffic spike handling
- NVIDIA HGX H100 on-demand ($5.49/GPU/hr)
- NVIDIA HGX B200 on-demand ($8.99/GPU/hr)
- NVIDIA HGX H200 (contact us)
- NVIDIA HGX B300 (contact us)
- NVIDIA GB200 NVL72 (contact us)
- NVIDIA GB300 NVL72 (contact us)
- Reserved capacity available
GPU Clusters
- On-demand pay-as-you-go GPU capacity (hourly)
- Reserved capacity (7-30 days, 31-90 days, 91-180 days, 181+ days)
- NVIDIA HGX H100 on-demand ($3.99/GPU/hr)
- NVIDIA HGX H200 on-demand ($5.99/GPU/hr)
- NVIDIA HGX B200 on-demand ($8.19/GPU/hr)
- NVIDIA GB200 NVL72 (contact us)
- NVIDIA GB300 NVL72 (contact us)
Sandbox
- Code Sandbox: VM sandboxes for large development environments ($0.0446/vCPU/hr, $0.0149/GiB RAM/hr)
- Code Interpreter: Execute LLM-generated code securely via API ($0.03/session)
Storage
- Shared Filesystem ($0.16/GiB/month)
- High-bandwidth, parallel filesystem colocated with compute
Fine-Tuning
- Supervised Fine-Tuning (LoRA)
- Supervised Fine-Tuning (Full Fine-Tuning)
- Direct Preference Optimization (LoRA)
- Direct Preference Optimization (Full Fine-Tuning)
- Standard pricing for models up to 100B parameters
- Specialized pricing for DeepSeek, GLM, Kimi, Llama 4, Qwen3, and other large models
- Minimum charge per job: $4.00 (standard)
Baseten vs Together AI FAQ
- Which one is cheaper?
- One or both use custom pricing, so it depends on your specific needs.
- Can I use either one for free?
- Baseten has a free plan. Together AI doesn't — you'll need to pay from day one.
- How do they charge?
- Both use a usage-based model, so the comparison is straightforward — it comes down to features and limits at each price point.
- Which one is a better deal?
- Depends on what you need. Baseten: They're competing in the ML inference infrastructure space against Replicate, Modal, and cloud-native options like AWS SageMaker — positioned as a developer-friendly middle ground that's more flexible than managed APIs but less DIY than raw cloud. The GPU pricing is granular enough to appeal to cost-conscious ML teams who want to optimize spend. Together AI: Together AI is pitching itself as the serious infrastructure layer for AI builders — not the cheapest (Replicate or self-hosting can undercut on specific models), but more flexible and enterprise-ready than most managed inference APIs. At $5.49/GPU/hr for H100 dedicated, they're competitive with CoreWeave and Lambda Labs while bundling more managed services around it.
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