Anthropic vs Baidu ERNIE: Token Pricing, Speed & Intelligence
Full comparison of Anthropic and Baidu ERNIE — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Anthropic
Claude 5 — Fable 5.1, Opus 5, Sonnet 5, Haiku 4.5 with 1M context
Anthropic builds the Claude model family, now in its fifth generation. The Claude 5 lineup includes Fable 5.1 and Opus 5 at the frontier (1M+ token context, reasoning models), Claude Sonnet 5 for production workloads, and Haiku 4.5 for cost-efficient inference. Anthropic also offers Claude Code (agentic coding) and Claude Science (research) as specialised products. Prompt caching is available at up to 90% discount.
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
Anthropic
Baidu ERNIE
Key differentiators
Claude 5 Opus and Fable 5 lead the BenchLM leaderboard as of September 2026, with 1M+ context windows and extended reasoning — plus Claude Code for agentic software engineering.
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
Anthropic FAQs
What are the latest Anthropic Claude models?
The Claude 5 family includes Fable 5.1 and Opus 5 (frontier reasoning), Claude Sonnet 5 (balanced), and Haiku 4.5 (efficient tier). Claude Code is a specialised agentic coding product. Check docs.anthropic.com/en/docs/about-claude/models for current pricing.
What is the context window for Claude 5 models?
Claude 5 Opus, Fable 5, and Mythos 5 all support 1M+ token context windows, enabling full-codebase and book-length document analysis in a single call.
How does Anthropic prompt caching work?
Anthropic's prompt caching lets you mark portions of your prompt (system prompts, documents, tool definitions) to be cached server-side. Cached tokens are billed at 10% of the standard input price after the first write, making repeated long-context calls dramatically cheaper.
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
Anthropic — Claude 5 — Fable 5.1, Opus 5, Sonnet 5, Haiku 4.5 with 1M context
Anthropic builds the Claude model family, now in its fifth generation. The Claude 5 lineup includes Fable 5.1 and Opus 5 at the frontier (1M+ token context, reasoning models), Claude Sonnet 5 for production workloads, and Haiku 4.5 for cost-efficient inference. Anthropic also offers Claude Code (agentic coding) and Claude Science (research) as specialised products. Prompt caching is available at up to 90% discount.
Claude 5 Opus and Fable 5 lead the BenchLM leaderboard as of September 2026, with 1M+ context windows and extended reasoning — plus Claude Code for agentic software engineering.
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
Anthropic
- Claude 5 family leads on coding and reasoning benchmarks
- 1M+ token context window on Claude 5 models
- Aggressive prompt caching — up to 90% discount
- No open-weight models — full vendor lock-in
- Frontier models are among the higher-priced options — check live table for current rates
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
Anthropic
- No open-weight models — full vendor lock-in
- Frontier models are among the higher-priced options — check live table for current rates
- No native image generation capability
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
Anthropic is a frontier lab, founded in 2021. Baidu ERNIE is a frontier lab, founded in 2000. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Anthropic and Baidu ERNIE are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Anthropic leads on claude 5 family leads on coding and reasoning benchmarks, while Baidu ERNIE leads on strong chinese-english bilingual performance — best-in-class for chinese language tasks. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.