HAI by HCloud vs Stability AI: Token Pricing, Speed & Intelligence
Full comparison of HAI by HCloud and Stability AI — 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.
Stability AI
Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation
Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.
Key metric comparison
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Live token pricing
Strengths and weaknesses
HAI by HCloud
Stability AI
Key differentiators
Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.
Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.
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.
Stability AI FAQs
What is Stable Diffusion 3.5?
Stable Diffusion 3.5 is Stability AI's latest generation of open-weight text-to-image models. SD 3.5 Large offers the highest quality; SD 3.5 Medium is a balanced option for production use. Both are available for self-hosting.
How does Stability AI compare to FLUX?
FLUX 1.1 Pro generally outperforms SD 3.5 on photorealism and prompt adherence benchmarks. However, SD 3.5 has a much larger community ecosystem of fine-tuned variants and LoRAs, making it more flexible for specialised use cases.
Can I self-host Stable Diffusion 3.5?
Yes. SD 3.5 Large and Medium weights are publicly available under the Stability AI Community License. You can run them on any GPU with sufficient VRAM — SD 3.5 Medium requires ~8GB VRAM; SD 3.5 Large requires ~24GB.
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.
Stability AI — Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation
Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.
Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.
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
Stability AI
- Open-weight SD 3.5 models — self-host on any GPU cloud
- Largest community ecosystem of fine-tuned variants and LoRAs
- Stable Image Ultra for photorealistic output
- Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
- Company has faced financial challenges and leadership changes
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
Stability AI
- Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
- Company has faced financial challenges and leadership changes
- SD 3.5 adoption slower than FLUX in the community
Provider category context
HAI by HCloud is a inference api, founded in 2024. Stability AI is a frontier lab, founded in 2020. HAI by HCloud as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. Stability AI as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose HAI by HCloud if you need Privacy-sensitive workloads. Choose Stability AI if you need open-weight sd 3.5 models — self-host on any gpu cloud. 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.