127 个模型 · 52 个提供商 · 199 个映射

开放注册表
面向 AI 基础设施

基于来源透明的价格、上下文限制、能力、访问条款和部署数据,发现并比较模型、提供商、MCP 服务器和智能体 Skills。

覆盖整个生态系统的提供商

OpenAI
Anthropic
Google
AWS Bedrock
Meta
Groq
Mistral
DeepSeek
xAI
IBM
Azure AI
Cohere
NVIDIA
Alibaba
Xiaomi
Hugging Face
Together AI
Fireworks
Replicate
SambaNova
Scaleway
Nebius
OpenAI
Anthropic
Google
AWS Bedrock
Meta
Groq
Mistral
DeepSeek
xAI
IBM
Azure AI
Cohere
NVIDIA
Alibaba
Xiaomi
Hugging Face
Together AI
Fireworks
Replicate
SambaNova
Scaleway
Nebius

127

模型

52

提供商

199

提供商映射

$8.04

每百万 Token 平均价格

热门模型

按相关性和提供商可用性排序的热门模型

查看全部 →

Claude Fable 5

Anthropic's first publicly available Mythos-class model, exceeding the capabilities of any model the company has previously made generally available. State-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, vision, and scientific research. Its lead grows on longer and more complex tasks. Ships with built-in safeguards that route sensitive cybersecurity, biology, chemistry, and distillation queries to Claude Opus 4.8.

上下文
300K
发布日期
2026年6月

GPT-5.6 Terra

The balanced tier of OpenAI's GPT-5.6 series, trading a small amount of peak quality for markedly lower latency and cost. Retains strong reasoning, coding, and agentic tool use with configurable reasoning effort, making it a default choice for production workloads that need frontier capability at scale.

上下文
1.0M
发布日期
2026年7月

Grok 4.5

xAI's strongest model to date, built to excel at coding, agentic tasks, and knowledge work and co-developed alongside coding tools for real-world software engineering. Features real-time information access, extended reasoning, and large-context tool use with an OpenAI-compatible API.

上下文
500K
发布日期
2026年7月

Claude Opus 4.8

Anthropic's most advanced model, building on Opus 4.7 with improvements across benchmarks in coding, agentic skills, reasoning, and knowledge work. Features enhanced honesty, better tool use efficiency, dynamic workflows support, and improved alignment.

上下文
300K
发布日期
2026年5月

GPT-5.5 Pro

OpenAI's premium tier model with extended reasoning capabilities, higher accuracy on complex tasks, and priority access. Optimized for professional and enterprise workloads requiring maximum quality.

上下文
256K
发布日期
2026年3月

Gemini 3.1 Pro

Google's latest flagship multimodal model with state-of-the-art performance on reasoning, coding, and multimodal understanding. Features native tool use, grounding, and million-token context window.

上下文
2.0M
发布日期
2026年3月

DeepSeek R1

DeepSeek's reasoning-focused model trained with reinforcement learning for complex multi-step reasoning. Excels at math, science, and coding problems requiring chain-of-thought reasoning.

上下文
131K
发布日期
2025年1月

DeepSeek V4

DeepSeek's fourth-generation model with improved mixture-of-experts architecture, enhanced reasoning and coding capabilities, and stronger multilingual performance. Competitive with frontier proprietary models.

上下文
256K
发布日期
2026年2月

Nemotron 3 Ultra

NVIDIA's flagship open 550B-parameter Mixture-of-Experts model with 55B active parameters, built for frontier reasoning and orchestration in long-running agentic systems. Features hybrid Mamba-Transformer architecture, LatentMoE routing, multi-token prediction, and NVFP4 precision for 5x higher throughput. Achieves 30% lower cost-to-task-completion on agentic benchmarks. Supports 1M+ token context window with 95% accuracy on Ruler@1M.

上下文
1.0M
发布日期
2026年6月

Gemma 4 31B

Google's flagship open-weight dense model with 31B parameters. All parameters active per forward pass. Ranks among top open models with strong performance on AIME 2026 (89.2%) and MMLU Pro (85.2%). Supports vision and extended context.

上下文
262K
发布日期
2026年4月

DeepSeek V4 Flash

DeepSeek's efficient V4 model with 284B total parameters (13B activated). Optimized for speed and cost-efficiency while maintaining strong performance. Supports 1M token context window.

上下文
1.0M
发布日期
2026年4月

Mistral Medium 3.5

Mistral AI's balanced model offering strong multilingual performance with excellent price-performance ratio. Optimized for production workloads requiring reliable quality across European and global languages.

上下文
128K
发布日期
2026年2月

模型比较

先明确任务,再选择模型。

把模型注册表转化为决策工具。筛选完整目录,并排比较可信数据,再根据自己的假设计算成本。

1

比较真正重要的数据

在一个视图中查看上下文、模态、能力、访问条款和提供商可用性。

2

价格始终归属于具体提供商

特定部署的输入与输出价格不会被当作模型的全局属性。

3

估算实际工作负载成本

使用自己的 Token 用量、缓存假设和请求次数,而不是抽象评分。

实时注册表快照

已记录的最大上下文窗口

注册表中的模型级容量。容量不代表质量。

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