Amazon Bedrock vs Baidu ERNIE: Token Pricing, Speed & Intelligence
Full comparison of Amazon Bedrock and Baidu ERNIE — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
Baidu ERNIE
ERNIE 5 — Baidu's frontier Chinese-English bilingual LLM API
Baidu ERNIE is the LLM API from Baidu, China's largest search company. The ERNIE 5 series includes ERNIE-5.1 (balanced) and ERNIE-5.0 (frontier), both optimised for Chinese-English bilingual tasks, knowledge retrieval, and enterprise applications. Pricing is in USD via the international API.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Amazon Bedrock
Baidu ERNIE
Key differentiators
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.
ERNIE 5 is the leading Chinese-English bilingual LLM API, backed by Baidu's search knowledge graph — the go-to choice for applications targeting Chinese-language users.
Frequently asked questions
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.
Baidu ERNIE FAQs
What is ERNIE?
ERNIE (Enhanced Representation through Knowledge Integration) is Baidu's LLM series. ERNIE 5 is the current generation, with ERNIE-5.1 (balanced) and ERNIE-5.0 (frontier) available via the Wenxin Qianfan API.
How much does the ERNIE API cost?
ERNIE-5.1 is $0.56/$2.53 per 1M input/output tokens. ERNIE-5.0 is $1.40/$5.60 per 1M tokens. See the Baidu Cloud pricing page for current rates.
Is ERNIE good for English tasks?
ERNIE 5 handles English competently but is primarily optimised for Chinese. For English-only workloads, frontier Western models typically outperform ERNIE. For Chinese or bilingual Chinese-English tasks, ERNIE is among the strongest options available.
Provider resources
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.
Baidu ERNIE — ERNIE 5 — Baidu's frontier Chinese-English bilingual LLM API
Baidu ERNIE is the LLM API from Baidu, China's largest search company. The ERNIE 5 series includes ERNIE-5.1 (balanced) and ERNIE-5.0 (frontier), both optimised for Chinese-English bilingual tasks, knowledge retrieval, and enterprise applications. Pricing is in USD via the international API.
ERNIE 5 is the leading Chinese-English bilingual LLM API, backed by Baidu's search knowledge graph — the go-to choice for applications targeting Chinese-language users.
Key strengths compared
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
Baidu ERNIE
- Strong Chinese-English bilingual performance — best-in-class for Chinese language tasks
- Deep integration with Baidu Search knowledge graph
- ERNIE-5.1 at $0.56/$2.53 per 1M tokens is competitive for a frontier-tier bilingual model
- Primarily optimised for Chinese — English performance trails frontier Western models
- Limited ecosystem outside China; fewer third-party integrations
Key weaknesses compared
Amazon Bedrock
- More complex setup than standalone inference APIs
- Pricing can be higher than direct provider APIs
- Latency overhead from AWS abstraction layer
Baidu ERNIE
- Primarily optimised for Chinese — English performance trails frontier Western models
- Limited ecosystem outside China; fewer third-party integrations
- Documentation and support primarily in Chinese
Provider category context
Amazon Bedrock is a cloud, founded in 2023. Baidu ERNIE is a frontier lab, founded in 2000. 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 Amazon Bedrock if you need native aws integration — iam, vpc, cloudwatch, s3. Choose Baidu ERNIE if you need Chinese NLP. 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.