Crusoe Managed Inference vs HAI by HCloud: Token Pricing, Speed & Intelligence
Full comparison of Crusoe Managed Inference 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.
Crusoe Managed Inference
Managed inference on Crusoe Cloud — DeepSeek V4, Gemma 4, GLM 5.1, Llama 3.3, Qwen3
Crusoe Managed Inference is the serverless LLM inference service from Crusoe Cloud, offering a curated catalog of open-weight models including DeepSeek V4 Pro/Flash, Gemma 4 31B, GLM 5.1, gpt-oss-120b, Llama 3.3 70B, and Qwen3 235B A22B. Crusoe Cloud is known for its clean-energy GPU infrastructure. Pricing is published at crusoe.ai/cloud/managed-inference.
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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Live token pricing
Strengths and weaknesses
Crusoe Managed Inference
HAI by HCloud
Key differentiators
Managed inference on Crusoe Cloud's clean-energy GPU infrastructure — competitive pricing on DeepSeek V4, Gemma 4, GLM 5.1, and Qwen3 without managing GPU clusters.
Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.
Frequently asked questions
Crusoe Managed Inference FAQs
What is Crusoe Managed Inference?
Crusoe Managed Inference is the serverless LLM API from Crusoe Cloud, offering open-weight models including DeepSeek V4 Pro/Flash, Gemma 4 31B, GLM 5.1, gpt-oss-120b, Llama 3.3 70B, and Qwen3 235B A22B. See crusoe.ai/cloud/managed-inference for current rates.
How much does Crusoe Managed Inference cost?
As of October 2026: DeepSeek V3 0324 $0.50/$1.50, DeepSeek V4 Flash $0.14/$0.28, DeepSeek V4 Pro $1.74/$3.48, Gemma 4 31B $0.14/$0.40, GLM 5.1 $1.20/$4.40, gpt-oss-120b $0.05/$0.20, Llama 3.3 70B $0.25/$0.75, Qwen3 235B A22B 2507 $0.22/$0.80. See crusoe.ai/cloud/managed-inference for current rates.
Is Crusoe Cloud clean energy?
Yes. Crusoe Cloud is known for using stranded and flared gas to power its GPU infrastructure, reducing the carbon footprint of AI compute compared to conventional data centers.
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
Crusoe Managed Inference — Managed inference on Crusoe Cloud — DeepSeek V4, Gemma 4, GLM 5.1, Llama 3.3, Qwen3
Crusoe Managed Inference is the serverless LLM inference service from Crusoe Cloud, offering a curated catalog of open-weight models including DeepSeek V4 Pro/Flash, Gemma 4 31B, GLM 5.1, gpt-oss-120b, Llama 3.3 70B, and Qwen3 235B A22B. Crusoe Cloud is known for its clean-energy GPU infrastructure. Pricing is published at crusoe.ai/cloud/managed-inference.
Managed inference on Crusoe Cloud's clean-energy GPU infrastructure — competitive pricing on DeepSeek V4, Gemma 4, GLM 5.1, and Qwen3 without managing GPU clusters.
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.
Key strengths compared
Crusoe Managed Inference
- Clean-energy GPU infrastructure — stranded and flared gas power
- Curated open-weight model catalog: DeepSeek V4, Gemma 4, GLM 5.1, Llama 3.3, Qwen3
- Competitive pricing on flagship open-weight models
- Smaller model catalog than Together AI or Fireworks
- No proprietary frontier models
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
Crusoe Managed Inference
- Smaller model catalog than Together AI or Fireworks
- No proprietary frontier models
- Less mature inference platform than dedicated inference providers
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
Crusoe Managed Inference is a cloud, founded in 2020. HAI by HCloud is a inference api, founded in 2024. 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 Crusoe Managed Inference if you need clean-energy gpu infrastructure — stranded and flared gas power. Choose HAI by HCloud if you need Privacy-sensitive workloads. 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.