Baseten vs HAI by HCloud: Token Pricing, Speed & Intelligence
Full comparison of Baseten and HAI by HCloud — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Baseten
Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection
Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.
HAI by HCloud
Japan-based inference — zero data retention, JPY pricing, TEE-secured Kimi K3
HAI is HCloud's LLM inference platform based in Japan, offering DeepSeek, GLM-5.3, Kimi K3, and Gemma 4 models with a zero data retention policy. Prices are in JPY per 1M tokens, tax included. The Kimi K3 (TEE) variant runs in a Trusted Execution Environment for confidential inference. Suited for Japanese enterprises and APAC workloads requiring data residency.
Key metric comparison
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131K
Live token pricing
No live pricing data available.
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| Model | Input | Output |
|---|---|---|
| DeepSeek V4.1 Flash 1017 | $60.00EST Oct 2026 | $240.00 |
| GLM-5.3 | $280.00EST Oct 2026 | $880.00 |
| Kimi K3 (TEE) | $585.00EST Oct 2026 | $2910.00 |
| Gemma 4 31B | $55.00EST Oct 2026 | $125.00 |
Strengths and weaknesses
Baseten
HAI by HCloud
Key differentiators
The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.
Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.
Frequently asked questions
Baseten FAQs
What is Baseten?
Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.
How does Baseten differ from Together AI or Replicate?
Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.
What GPUs does Baseten support?
Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.
HAI by HCloud FAQs
What is HAI by HCloud?
HAI is HCloud's LLM inference API based in Japan. It offers DeepSeek V4.1 Flash, GLM-5.3, Kimi K3 (TEE), and Gemma 4 31B with a zero data retention policy and JPY pricing. See hai.hcloud.ltd/pricing for current rates.
What is the Kimi K3 TEE variant?
The Kimi K3 (TEE) variant runs inside a Trusted Execution Environment, providing hardware-level isolation for confidential inference. This is suited for workloads where prompt and response data must not be accessible to the infrastructure operator.
Does HAI retain my data?
No. HAI operates a zero data retention policy — prompts and responses are not stored after the request completes.
Provider resources
Key strengths compared
Baseten
- Full control over model serving: custom preprocessing, postprocessing, and business logic
- Bring your own weights — deploy any HuggingFace model or custom fine-tune
- GPU selection: H100, A100, A10G, T4 with per-second billing
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
HAI by HCloud
- Zero data retention policy — suitable for privacy-sensitive workloads
- Japan-based infrastructure — low latency for APAC users
- TEE-secured Kimi K3 variant for confidential inference
- JPY pricing excluded from USD cross-provider comparisons
- Smaller catalog vs global inference hubs
Key weaknesses compared
Baseten
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
- Pricing is higher than shared inference APIs for low-volume workloads
HAI by HCloud
- JPY pricing excluded from USD cross-provider comparisons
- Smaller catalog vs global inference hubs
- Newer provider — limited third-party benchmark transparency
Provider category context
Baseten is a inference api, founded in 2019. HAI by HCloud is a inference api, founded in 2024. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Baseten and HAI by HCloud host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.