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AI21 Labs vs HAI by HCloud: Token Pricing, Speed & Intelligence

Full comparison of AI21 Labs 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.

AI21 Labs

Jamba 1.6 — hybrid SSM-Transformer models with 256K context

AI21 Labs develops the Jamba model family, which uses a hybrid SSM (Mamba) and Transformer architecture. Jamba 1.6 Large and Mini offer 256K token context windows at competitive prices. The hybrid architecture delivers faster inference and lower memory usage than pure-Transformer models of comparable size.

Long-context chatDocument analysisSummarisationCost-sensitive inference
Proprietary models

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.

Privacy-sensitive workloadsAPAC / Japan deploymentsConfidential inference
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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Live token pricing

Strengths and weaknesses

AI21 Labs

Hybrid SSM-Transformer architecture delivers faster inference than pure-Transformer models
256K token context window on both Jamba 1.6 Large and Mini
Jamba 1.6 Mini at $0.20/$0.40 per 1M tokens is highly cost-competitive
Strong performance on long-document tasks due to SSM efficiency
Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
Less ecosystem support than OpenAI-compatible providers
No image, audio, or multimodal 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 — no currency conversion risk for Japanese customers
JPY pricing excluded from USD cross-provider comparisons
Smaller catalog vs global inference hubs
Newer provider — limited third-party benchmark transparency

Key differentiators

AI21 Labs

Jamba's hybrid SSM-Transformer architecture enables 256K context at lower memory and latency cost than pure-Transformer models — with Jamba 1.6 Mini among the cheapest 256K-context options available.

HAI by HCloud

Japan-based inference with zero data retention and a TEE-secured Kimi K3 variant for confidential workloads.

Frequently asked questions

AI21 Labs FAQs

What is the Jamba architecture?

Jamba uses a hybrid of Mamba (SSM) and Transformer layers. This reduces memory usage and improves throughput on long sequences compared to pure-Transformer models, while maintaining strong reasoning performance.

How much does AI21 Labs API cost?

Jamba 1.6 Large is $2.00/$8.00 per 1M input/output tokens. Jamba 1.6 Mini is $0.20/$0.40 per 1M tokens. Both support 256K context. See ai21.com/pricing for current rates.

What context window does Jamba 1.6 support?

Both Jamba 1.6 Large and Jamba 1.6 Mini support 256K token context windows, making them suitable for long-document analysis and extended conversations.

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

AI21 Labs — Jamba 1.6 — hybrid SSM-Transformer models with 256K context

AI21 Labs develops the Jamba model family, which uses a hybrid SSM (Mamba) and Transformer architecture. Jamba 1.6 Large and Mini offer 256K token context windows at competitive prices. The hybrid architecture delivers faster inference and lower memory usage than pure-Transformer models of comparable size.

Jamba's hybrid SSM-Transformer architecture enables 256K context at lower memory and latency cost than pure-Transformer models — with Jamba 1.6 Mini among the cheapest 256K-context options available.

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

AI21 Labs

  • Hybrid SSM-Transformer architecture delivers faster inference than pure-Transformer models
  • 256K token context window on both Jamba 1.6 Large and Mini
  • Jamba 1.6 Mini at $0.20/$0.40 per 1M tokens is highly cost-competitive
  • Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
  • Less ecosystem support than OpenAI-compatible providers

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

AI21 Labs

  • Smaller model family than frontier labs — two models vs dozens at OpenAI or Anthropic
  • Less ecosystem support than OpenAI-compatible providers
  • No image, audio, or multimodal models

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

AI21 Labs is a frontier lab, founded in 2017. HAI by HCloud is a inference api, founded in 2024. AI21 Labs as a frontier lab trains and serves its own proprietary models. HAI by HCloud as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose AI21 Labs if you need Long-context tasks. 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.