HAI by HCloud vs Infermatic: Token Pricing, Speed & Intelligence
Full comparison of HAI by HCloud and Infermatic — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
Infermatic
Uncensored open-weight inference — RP, creative writing, and unrestricted model access
Infermatic is a specialized LLM inference provider focused on uncensored and minimally-filtered open-weight models, serving the roleplay, creative writing, and adult content communities. It hosts a curated catalog of fine-tuned Llama, Mistral, and Qwen variants optimized for creative and RP use cases, with OpenAI-compatible API access. Infermatic offers competitive per-token pricing with no content filtering on supported models, making it a go-to provider for use cases that mainstream APIs decline.
Key metric comparison
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Live token pricing
Strengths and weaknesses
HAI by HCloud
Infermatic
Key differentiators
Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.
The leading inference API for uncensored open-weight models — purpose-built for roleplay, creative writing, and adult content use cases that mainstream providers decline to serve.
Frequently asked questions
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.
Infermatic FAQs
What is Infermatic?
Infermatic is an LLM inference provider specializing in uncensored and minimally-filtered open-weight models for roleplay, creative writing, and adult content use cases. It offers OpenAI-compatible API access to curated RP-optimized fine-tunes.
What models does Infermatic offer?
Infermatic hosts RP-optimized fine-tunes of Llama 4, Mistral, Qwen3, and other open-weight base models. The catalog focuses on models fine-tuned for creative writing, character roleplay, and adult content generation.
Is Infermatic API OpenAI-compatible?
Yes. Infermatic provides an OpenAI-compatible REST API, so you can use it as a drop-in replacement in any application that supports custom base URLs — including LangChain, LlamaIndex, and most AI frameworks.
Provider resources
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.
Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.
Infermatic — Uncensored open-weight inference — RP, creative writing, and unrestricted model access
Infermatic is a specialized LLM inference provider focused on uncensored and minimally-filtered open-weight models, serving the roleplay, creative writing, and adult content communities. It hosts a curated catalog of fine-tuned Llama, Mistral, and Qwen variants optimized for creative and RP use cases, with OpenAI-compatible API access. Infermatic offers competitive per-token pricing with no content filtering on supported models, making it a go-to provider for use cases that mainstream APIs decline.
The leading inference API for uncensored open-weight models — purpose-built for roleplay, creative writing, and adult content use cases that mainstream providers decline to serve.
Key strengths compared
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
Infermatic
- Uncensored and minimally-filtered model access for creative and RP use cases
- Curated catalog of RP-optimized fine-tunes (Llama, Mistral, Qwen variants)
- OpenAI-compatible API — easy integration with existing tooling
- Not suitable for enterprise or compliance-sensitive workloads
- Smaller model catalog than Together AI or OpenRouter
Key weaknesses compared
HAI by HCloud
- JPY pricing excluded from USD cross-provider comparisons
- Smaller catalog vs global inference hubs
- Newer provider — limited third-party benchmark transparency
Infermatic
- Not suitable for enterprise or compliance-sensitive workloads
- Smaller model catalog than Together AI or OpenRouter
- Less infrastructure redundancy than larger providers
Provider category context
HAI by HCloud is a inference api, founded in 2024. Infermatic is a open source host, founded in 2023. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.
How to choose between them
Choose HAI by HCloud if you need Privacy-sensitive workloads. Choose Infermatic if you need uncensored and minimally-filtered model access for creative and rp use cases. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.