ERNIE 5.1 Thinking is the latest Wenxin model with explicit reasoning enabled for harder planning, coding, math, and agentic tasks. ⚠️ Note: privacy and logging guarantees may be limited.
Added May 10, 2026
Context Window
119.0K
Max Output
64.0K
Input Price (Auto)
$0.75/1M
Output Price (Auto)
$3.00/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
No benchmark data is available yet for this model.
Providers
Auto routing is available for this model. Explicit provider selection is not available.
Loading provider options…
Related text models
Compare ERNIE 5.1 Thinking with similar models from the same provider or model family.
ERNIE 5.1
ernie-5.1ERNIE 5.1 is the latest Wenxin model, with broad upgrades to agentic workflows, knowledge, reasoning, and deep search. ⚠️ Note: privacy and logging guarantees may be limited.
Ernie 5.0 Thinking Preview
ernie-5.0-thinking-previewERNIE 5.0 Thinking is Baidu's next-generation step-by-step reasoning model, providing stronger logical thinking, code generation, and tool-use capabilities with explicit thinking traces. ⚠️ Note: This model routes through Baidu, a Chinese entity - privacy and logging guarantees may be limited.
ERNIE X1.1
ernie-x1.1-previewThe Wenxin large model X1.1 has made significant improvements in question answering, tool invocation, intelligent agents, instruction following, logical reasoning, mathematics, and coding tasks, with notable enhancements in factual accuracy. The context length has been extended to 64K tokens, supporting longer inputs and dialogue history, which improves the coherence of long-chain reasoning while maintaining response speed. ⚠️ Note: This model routes through Baidu (China) — privacy and logging guarantees may be limited.
Schematron V2 Small
inference-net/schematron-v2-smallInference.net's 3B-parameter HTML-to-JSON extraction model, focused on accuracy for complex schemas and long web pages. It turns HTML into typed, structured data for web scraping and product catalog ingestion, with a 128K-token context window. Supply HTML in the user message and extraction instructions in a JSON schema via response_format; it does not follow ordinary chat or system prompts.
Schematron V2 Turbo
inference-net/schematron-v2-turboInference.net's 3B-parameter HTML-to-JSON extraction model, optimized for throughput and low cost on high-volume workloads. It turns HTML into typed, structured data for web scraping and product catalog ingestion, with a 128K-token context window. Supply HTML in the user message and extraction instructions in a JSON schema via response_format; it does not follow ordinary chat or system prompts.
DeepSeek V4.1 Flash TEE
TEE/deepseek-v4.1-flashDeepSeek V4.1 Flash supports text and image input, reasoning, tool calling, and structured output with a 1M-token context window. This route runs through Tinfoil attested inference inside a Trusted Execution Environment.