AI21 Labs vs Amazon Bedrock: Token Pricing, Speed & Intelligence
Full comparison of AI21 Labs and Amazon Bedrock — 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.
Amazon Bedrock
AWS-native LLM access — Nova, Claude, Llama, DeepSeek, MiniMax, Kimi and more
Amazon Bedrock is AWS's managed LLM service, providing access to Amazon's own Nova models alongside third-party models from Anthropic, Meta, Mistral, and others. The 2026 catalog has expanded to include DeepSeek v3.2, MiniMax M1, Moonshot Kimi 3, Z.AI GLM 5, and Writer Palmyra. It integrates natively with the AWS ecosystem including IAM, VPC, and CloudWatch, making it the default choice for teams already on AWS.
Key metric comparison
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Live token pricing
Strengths and weaknesses
AI21 Labs
Amazon Bedrock
Key differentiators
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.
Run Claude, Llama, DeepSeek, and Amazon Nova within your own AWS VPC — data never leaves your account, with a broad third-party model catalog available through a single API.
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.
Amazon Bedrock FAQs
What models are available on Amazon Bedrock in 2026?
Amazon Bedrock offers Amazon Nova (Micro, Lite, Pro), Anthropic Claude 5 family, Meta Llama 4, Mistral, Cohere, DeepSeek v3.2, MiniMax M1, Moonshot Kimi 3, Z.AI GLM 5, Writer Palmyra, and others. The catalog varies by AWS region.
How does Amazon Bedrock pricing work?
Bedrock uses on-demand pricing per 1M tokens, similar to direct provider APIs. Provisioned Throughput is available for reserved capacity at a fixed hourly rate. Prices are generally comparable to or slightly above direct provider pricing.
Is Amazon Bedrock HIPAA-compliant?
Yes. Amazon Bedrock is covered under AWS's HIPAA BAA, making it suitable for healthcare applications that require HIPAA compliance. Data processed through Bedrock stays within your AWS account.
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.
Amazon Bedrock — AWS-native LLM access — Nova, Claude, Llama, DeepSeek, MiniMax, Kimi and more
Amazon Bedrock is AWS's managed LLM service, providing access to Amazon's own Nova models alongside third-party models from Anthropic, Meta, Mistral, and others. The 2026 catalog has expanded to include DeepSeek v3.2, MiniMax M1, Moonshot Kimi 3, Z.AI GLM 5, and Writer Palmyra. It integrates natively with the AWS ecosystem including IAM, VPC, and CloudWatch, making it the default choice for teams already on AWS.
Run Claude, Llama, DeepSeek, and Amazon Nova within your own AWS VPC — data never leaves your account, with a broad third-party model catalog available through a single API.
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
Amazon Bedrock
- Native AWS integration — IAM, VPC, CloudWatch, S3
- Expanded 2026 catalog: DeepSeek v3.2, MiniMax, Kimi 3, Z.AI GLM 5, Writer Palmyra
- Access to Claude, Llama, Mistral, and Amazon Nova via one API
- More complex setup than standalone inference APIs
- Pricing can be higher than direct provider APIs
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
Amazon Bedrock
- More complex setup than standalone inference APIs
- Pricing can be higher than direct provider APIs
- Latency overhead from AWS abstraction layer
Provider category context
AI21 Labs is a frontier lab, founded in 2017. Amazon Bedrock is a cloud, 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 AI21 Labs if you need Long-context tasks. Choose Amazon Bedrock if you need native aws integration — iam, vpc, cloudwatch, s3. 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.