AI Model Comparison

Anthropic's fastest and cheapest model, ideal for real-time conversations and high-frequency API calls with extremely low cost.

Anthropic's strongest coding model, ranked first on SWE-bench, with top-tier code quality and instruction-following capabilities, excelling in agent tasks.

Claude Haiku 4.5, the fastest Claude, with near-frontier intelligence and 200K context, ideal for high-concurrency and low-latency scenarios.

Claude Opus 4.5, 200K context, high-quality reasoning and coding, relatively better cost-effectiveness.

Claude Opus 4.6, 1M context, supports extended thinking, stable performance on complex tasks.

Claude Opus, the previous generation flagship, offers 1M context, strong complex reasoning and agentic coding capabilities, and remains a top-tier choice.

Anthropic's current strongest model, top-tier in complex reasoning, long-cycle agentic coding, and highly autonomous tasks, ranked first in the Intelligence Index.

Claude Sonnet 4.5, with 200K context, balances speed and intelligence, excelling in coding and agent tasks.

The best balance of speed and intelligence, with 1M context, offering great value for daily development and agent tasks.

OpenAI's flagship multimodal model, proficient in vision, speech, and text, with fast response speed and the most comprehensive ecosystem.

GPT-4o Lite, 3x faster than GPT-4o with 95% cost reduction, ideal for high-concurrency agent scenarios.

OpenAI's current flagship, ranked second on the Intelligence Index (just behind Claude Opus 4.8), with top-tier performance in high/ultra-high reasoning settings.

OpenAI's specialized reasoning model, answers after deep thinking, performs best on complex math/science/code problems, but is slow.

OpenAI o-series reasoning model, answers after deep thinking, performs strongly on complex math/science/coding problems.

Google's ultra-long context specialized model with a 2 million token window, capable of analyzing entire codebases or long videos.

Google's latest agentic model with million-token ultra-long context, native tool calling support, and extremely low price.

Google's flagship, with ultra-long context, native multimodal capabilities, and tool calling, its reasoning ability ranks among the top tier.

Gemini Fast: excellent speed and cost, ideal for high concurrency and real-time scenarios.

DeepSeek's fast open-source model with 1M context and extremely low price, suitable for large-scale batch processing.

China's open-source flagship, with 1M context and dual thinking/non-thinking modes, excels in coding and reasoning, priced at a fraction of closed-source flagships.

Designed for complex reasoning, with math/logic/coding capabilities comparable to o1, but fully open-source with training costs at only 3%.

Domestic flagship model with code and math capabilities comparable to Claude, priced at only 5% of OpenAI, the king of cost-effectiveness.

Meta Llama 3.1 405B: A flagship open-source model with 405 billion parameters, 128K context, and performance approaching closed-source flagships.

Meta Llama 3.1 70B: A 70-billion-parameter open-source general-purpose model with 128K context, offering high deployment cost-effectiveness.

Meta Llama 3.1 8B: An 8-billion-parameter lightweight open-source model with 128K context, suitable for edge and low-cost deployment.

Meta's latest open-source flagship, 70 billion parameters, self-hostable, business-friendly license, performance approaching closed-source models.

Meta Llama 4 Maverick: 400B total params (17B activated, 128 experts) MoE, 1M context, open weights, commercially friendly.

Meta's latest open-source model features a native 10M ultra-long context, supports self-hosting, and is commercially friendly.

Alibaba's Tongyi Qianwen latest flagship, with the strongest Chinese language capabilities domestically, fully open-source, and supports multimodal.

Alibaba's specialized code model surpasses Claude 3.5 Sonnet in coding ability, achieving 98.5% on HumanEval, fully open-source.

Tongyi Qianwen 2.5 Max: A large-scale MoE flagship model with comprehensive capabilities comparable to mainstream closed-source models.

Tongyi Qianwen 3 Code Special: 480B-A35B MoE open source (Apache 2.0), strong code capabilities.

Tongyi Qianwen 3 Max: A closed-source flagship with over 1T parameters, representing the ceiling of the Tongyi series' capabilities.

Alibaba Tongyi Qianwen 3.5, open-source, fast, and extremely low-cost (starting from approximately $0.01/1M), available in multiple sizes.

Tongyi Qianwen 3.6: 35B-A3B MoE open-source model (Apache 2.0), the latest generation in 2026.

Tongyi Qianwen 3.6 Plus: Closed-source flagship version, released in 2026, with comprehensive capabilities comparable to mainstream closed-source models.

Zhipu GLM-4-Plus: Closed-source flagship version (2024) with strong overall capabilities.

Zhipu GLM-4.5: 128K context, comprehensive capabilities comparable to mainstream models, one of the leading domestic open-source models.

Zhipu GLM-4.6: 200K context (expanded from 128K in 4.5), token efficiency improved by approximately 30% compared to the previous generation.

Zhipu GLM-4.7: Open source (MIT), an iterative upgrade of GLM-4.6.

Zhipu GLM-5: The latest open-source flagship in 2026 (MIT), with comprehensive capabilities comparable to mainstream closed-source models.

Kimi K2: 128K–256K context, 1T total params (32B active) MoE, trained on 15.5T tokens, open-source weights.

Kimi K2 Thinking: 256K context, 1T parameters (32B activated) MoE, focused on deep reasoning, open-source weights.

Moonshot Kimi K2.5: 256K context, 1T total params (32B active) MoE + vision, open-source weights, multimodal upgrade of K2.

Moonshot Kimi series, one of the highest-ranked open-source weight models on the current Intelligence Index.

Step-2 by StepStar: a trillion-parameter LLM (2024), one of the representative domestic large models.

Step-3 by StepFun: A large model released in 2025, focusing on multimodality and large-scale parameters.

Step-3.5-Flash by Jieyue Xingchen: 196B-A11B MoE, 256K context, supports tool calling, open-source (Apache 2.0).

Step-3.7-Flash by Jieyue Xingchen: The latest open-source (Apache 2.0) fast model in 2026.

Mistral code-specific model, supporting 80+ programming languages, code completion and generation.

Europe's strongest AI model, with excellent multilingual capabilities and support for Function Calling, suitable for European compliance scenarios.

Mistral flagship, 128K context, strong multilingual and code capabilities, representative of European open-weight models.

Mistral's flagship MoE architecture open-source model, with 141 billion parameters and 39 billion activated, achieving the best balance between performance and cost.

Mistral classic MoE model, 8×7B experts, open-source, lightweight and efficient, widely deployed.

Tongyi Qianwen specialized open-source reasoning model with 32 billion parameters, excelling in mathematics and logical reasoning.