语言模型Liquid AI稳定版
LFM2-2.6B-Exp
RL-only post-trained 2.6B model with improved math and reasoning capabilities
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MoE 实验高效推理端侧部署
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端侧部署低延迟轻量模型
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端侧部署低延迟轻量模型
语言模型Liquid AI稳定版
LFM2-350M
Ultra-compact 350M parameter model for edge devices and low latency deployments
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端侧部署低延迟轻量模型
语言模型Liquid AI稳定版
LFM2-350M-ENJP-MT
350M parameter model for bidirectional English-Japanese translation
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端侧部署低延迟轻量模型
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数学推理教育场景轻量部署
语言模型Arcee AI预览版
Trinity Nano 6B
Pricing Integration List chevron-right Language Models chevron-right Trinity-Nano (6B) Trinity-Mini (26B) Trinity-Large-Preview Trinity-Large-Thinking API Reference chevron-right Your First API Call Chat Completion Usage Models Capabilities chevron-right Streaming Messages Multi-Turn Conversations Function Calling Structured Outputs Reasoning Traces Quick Deploys chevron-right Download Models arrow-up-right Hardware Prerequisites Consumer Hardware chevron-right Inference Engines chevron-right Policies chevron-right Deprecation Policy chevron-up chevron-down gitbook Powered by GitBook gitbook xmark block-quote On this page xmark xmark copy Copy chevron-down block-quote On this page block-quote Language Models Trinity-Nano (6B) Overview Trinity Nano is a 6B-parameter (1B active) sparse mixture-of-experts language model, optimized for high-efficiency inference in real-time, on-device, and embedded AI applications.
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端侧部署低延迟轻量 Agent
语言模型Arcee AI稳定版
Trinity Mini
Pricing Integration List chevron-right Language Models chevron-right Trinity-Nano (6B) Trinity-Mini (26B) Trinity-Large-Preview Trinity-Large-Thinking API Reference chevron-right Your First API Call Chat Completion Usage Models Capabilities chevron-right Streaming Messages Multi-Turn Conversations Function Calling Structured Outputs Reasoning Traces Quick Deploys chevron-right Download Models arrow-up-right Hardware Prerequisites Consumer Hardware chevron-right Inference Engines chevron-right Policies chevron-right Deprecation Policy chevron-up chevron-down gitbook Powered by GitBook gitbook xmark block-quote On this page xmark xmark copy Copy chevron-down block-quote On this page block-quote Language Models Trinity-Mini (26B) Overview Trinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model, engineered for efficient inference over long contexts with robust function calling and multi-step agent workflows.
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函数调用Agent 工作流长上下文
语言模型Arcee AI预览版
Trinity Large Preview
Pricing Integration List chevron-right Language Models chevron-right Trinity-Nano (6B) Trinity-Mini (26B) Trinity-Large-Preview Trinity-Large-Thinking API Reference chevron-right Your First API Call Chat Completion Usage Models Capabilities chevron-right Streaming Messages Multi-Turn Conversations Function Calling Structured Outputs Reasoning Traces Quick Deploys chevron-right Download Models arrow-up-right Hardware Prerequisites Consumer Hardware chevron-right Inference Engines chevron-right Policies chevron-right Deprecation Policy chevron-up chevron-down gitbook Powered by GitBook gitbook xmark block-quote On this page xmark xmark copy Copy chevron-down block-quote On this page block-quote Language Models Trinity-Large-Preview Overview Trinity Large (Preview) is a 400B-parameter (13B active) sparse mixture-of-experts language model, engineered to scale model capacity while maintaining inference efficiency over long contexts, with strong performance in reasoning-heavy workloads including math, coding-related tasks, and multi-step agent workflows.
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复杂任务编码推理高级 Agent
语言模型Arcee AI稳定版
Trinity Large Thinking
Pricing Integration List chevron-right Language Models chevron-right Trinity-Nano (6B) Trinity-Mini (26B) Trinity-Large-Preview Trinity-Large-Thinking API Reference chevron-right Your First API Call Chat Completion Usage Models Capabilities chevron-right Streaming Messages Multi-Turn Conversations Function Calling Structured Outputs Reasoning Traces Quick Deploys chevron-right Download Models arrow-up-right Hardware Prerequisites Consumer Hardware chevron-right Inference Engines chevron-right Policies chevron-right Deprecation Policy chevron-up chevron-down gitbook Powered by GitBook gitbook xmark block-quote On this page xmark xmark copy Copy chevron-down block-quote On this page block-quote Language Models Trinity-Large-Thinking Overview Trinity-Large-Thinking is a reasoning-optimized variant of Arcee AI's Trinity-Large family — a 398B-parameter sparse Mixture-of-Experts (MoE) model with approximately 13B active parameters per token. Built on Trinity-Large-Base and post-trained with extended chain-of-thought reasoning and agentic RL, Trinity-Large-Thinking delivers state-of-the-art performance on agentic benchmarks while maintaining strong general capabilities. Trinity-Large-Thinking generates explicit reasoning traces wrapped in <think>...</think> blocks before producing its final response. This thinking process is critical to the model's performance — thinking tokens must be kept in context for multi-turn conversations and agentic loops to function correctly.
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多步推理Reasoning TraceAgent 工作流
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$0.25 / 1M Tokens
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$0.75 / 1M Tokens
高并发推理Tool Calling低延迟自动化
语言模型Nous Research稳定版
Hermes-4-70B
This incarnation of Hermes 4 balances scale and size. It handles complex reasoning tasks, while staying fast and cost effective. A versatile choice for many use cases.
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通用推理成本敏感 API混合思考
语言模型Nous Research稳定版
Hermes-4-405B
This is the largest model in the Hermes 4 family, and it is the fullest expression of our design, focused on advanced reasoning and creative depth rather than optimizing inference speed or cost.
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高级推理创作写作复杂任务
语言模型Nous Research即将下线
Hermes-4.3-36B
Hermes 4.3 is optimised for local deployment. You can dowload it from Hugging Face for local use.
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