Baidu Provider

In addition to DeepSeek, TencentCloud and AlibabaCloud now also offer the official 0731 version, while other providers are still using the old 0424 version. . DeepSeek V4 Pro is DeepSeek’s flagship open-weight Mixture-of-Experts model, released in preview on April 24, 2026. It features 1.6 trillion total parameters, with 49 billion activated per token, and supports a one-million-token context window. Designed for advanced reasoning, coding, STEM tasks, and autonomous agents, it delivers state-of-the-art performance among open models and rivals leading proprietary systems. The model supports both thinking and non-thinking modes and is available through DeepSeek’s applications and APIs.

DeepSeek V4.1 Flash is a 552B-parameter MoE model built on a new causal encoder-decoder architecture, designed for higher capability, faster reasoning, higher throughput, and lower serving cost. It natively supports multimodal visual understanding and delivers flagship-level intelligence with significantly reduced KV cache requirements, making it well suited for high-throughput and cost-sensitive agentic workloads.

DeepSeek-V4-Flash is the efficiency-oriented variant of the DeepSeek V4 series, released as a preview and open-sourced alongside the flagship V4-Pro. It is designed for developers who need the V4 generation's long-context and reasoning capability at a faster, more economical API tier. Compared with V4-Pro, V4-Flash uses smaller total parameters and active parameters, resulting in faster response times and lower API cost. It retains reasoning capability close to V4-Pro and matches V4-Pro on simple agent tasks, with a measurable gap appearing only on the most demanding agent workflows. World knowledge is slightly below V4-Pro but remains competitive within the open-source landscape.

Like V4-Pro, V4-Flash inherits the new attention mechanism built on token-dimension compression and DeepSeek Sparse Attention (DSA), supports a 1M context window as standard, and offers both thinking and non-thinking modes with a reasoning_effort parameter (high / max).

Note on migration: the legacy model names deepseek-chat and deepseek-reasoner currently route to V4-Flash in non-thinking and thinking mode respectively, and will be retired on 2026-07-24. Existing integrations should migrate to the explicit model names deepseek-v4-flash or deepseek-v4-pro. The model is accessible via OpenAI ChatCompletions and Anthropic interfaces, with weights open-sourced on Hugging Face and ModelScope.

The new-generation Wenxin model, Wenxin 5.1, is a natively multimodal large model. It adopts a native unified multimodal modeling approach to jointly model text, images, audio, and video, providing comprehensive multimodal capabilities. Wenxin 5.1’s core abilities have been comprehensively upgraded and it performs excellently on benchmark datasets, with particularly strong results in multimodal understanding, instruction following, creative writing, factuality, agent planning, and tool use

The new-generation Wenxin model, Wenxin 5.0, is a natively multimodal large model. It adopts a native unified multimodal modeling approach to jointly model text, images, audio, and video, providing comprehensive multimodal capabilities. Wenxin 5.0’s core abilities have been comprehensively upgraded and it performs excellently on benchmark datasets, with particularly strong results in multimodal understanding, instruction following, creative writing, factuality, agent planning, and tool use

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

GLM-5.2 supports a larger context window and output length, with up to 1M context and 128K output tokens. It adds streaming output for tool calls via tool_stream=true, enabling real-time access to tool call arguments. Like the GLM-4.7 series, it supports deep thinking with thinking={ type: "enabled" }, where thinking is enforced once enabled, and introduces reasoning_effort to control reasoning intensity under chain-of-thought mode. It also delivers stronger coding performance and more advanced reasoning capabilities.

GLM-5.3 is Zhipu AI’s next-generation flagship text model, built on GLM-5.2 and enhanced through large-scale, long-horizon task post-training. It delivers an approximately 50% improvement in coding experience, autonomously handling complex project development, debugging, validation, and delivery. It also supports a 1-million-token context window, up to 128K-token outputs, tool calling, and MCP, with strong performance in cybersecurity tasks such as code review and vulnerability detection.

GLM-5.3-FlashX is a faster and smoother version of GLM-5.3-Flash, delivering inference speeds of up to 200 tokens/s. GLM-5.3-FlashX is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.