glm-5.3-flash

B.AI announced that the limited-time free trial of GLM-5.3-Flash is coming to an end. A special offer with a 90% discount will seamlessly take over starting from September 12 at 10:00 (SGT), where users only need to pay 10% of the original price, saving 90% directly, with input as low as $0.015/M and output as low as $0.05/M. As a native multimodal large model, GLM-5.3-Flash has a total of 320 billion parameters and 18 billion active parameters, combining sparse and linear attention mixed architecture with 1 million ultra-long context, performing strongly in scenarios such as programming development, agents, long context processing, and high-frequency API workloads. B.AI consistently practices the vision of universal computing power, adhering to low-threshold access, and is committed to allowing every developer to use top-tier computing power without burden at a highly competitive price, bidding farewell to high costs and accelerating innovation implementation.

On September 9, the official price adjustment for Zhipu GLM-5.3-Flash will take effect. The AI model invocation platform B.AI announced a limited-time extension of free benefits, available from now until September 12 at 09:59 (SGT), during which the model can still be fully invoked for free on the B.AI platform.GLM-5.3-Flash has a total parameter of 320B and an activation parameter of 18B, supporting 1M context. Models such as Qwen3.8 Flash, Hy3, and MiMo V2.5 remain freely accessible on the B.AI platform.

On September 8, B.AI, the intelligent global settlement layer connecting models, Agents, and value flow, announced that GLM-5.3-Flash will continue to provide free calling support for global developers after the official limited-time 50% discount ends at 24:00 on September 9. Developers will not need to change their usage habits due to upstream price adjustments.GLM-5.3-Flash is the leading model in terms of call volume on the current B.AI platform, with a total of 320 billion parameters and 18 billion active parameters, supporting 1 million ultra-long contexts, balancing rapid response and reasoning capabilities, and is used for code assistance, data processing, and text generation.

GLM-5.3-Flash has become the most frequently used and popular model on the B.AI platform, with a cumulative token throughput exceeding 2.41 trillion.As the first native multimodal model in the GLM-5 series, GLM-5.3-Flash features a total of 320 billion parameters and 18 billion active parameters, employing a hybrid architecture that combines sparse and linear attention, supporting 1 million ultra-long contexts, while ensuring rapid response, powerful reasoning, and high cost-effectiveness.Starting today, developers can still call this model for free through the B.AI platform, covering diverse scenarios such as high-frequency APIs, code writing, complex agents, and ultra-long document processing.

B.AI platform announced yesterday that its free model lineup is fully ready, covering six top models including GLM-5.3-Flash, DeepSeek-V4-Flash, DeepSeek-V4-Flash-Vision-Exp, Hy3 (Tencent Hunyuan), MiMo-V2.5 (Xiaomi), and Qwen3.8-Flash, all available to users with zero barriers for free.Among them, the debuting GLM-5.3-Flash is the "Ox Alpha" that has attracted widespread attention. As the first native multimodal model in the GLM-5 series, it features a total of 320B parameters and 18B active parameters, using a sparse + linear attention hybrid architecture and supporting 1M ultra-long context, combining rapid response with strong reasoning capabilities, making it the cost-effective choice for high-frequency calling scenarios. This free lineup covers various scenarios including pure text, multimodal, code generation, and Agent scheduling. Whether developers or deep AI users, they can access cutting-edge large model capabilities at zero cost through the B.AI platform, simply by logging in at chat.b.ai/chat to start an efficient workflow.

According to the Securities Times, on August 27, the reporter learned from SenseTime that SenseTime's large device provides domestic computing power support and Token services for the GLM-5.3-Flash recently launched and open-sourced by Zhipu, which is considered another benchmark for the large-scale commercial use of domestic computing power. It was revealed that the daily average Token service volume of SenseTime's large device reached 24.2 trillion in July, and it is expected to exceed a daily average of 100 trillion by the end of 2026.

On August 27, the one-stop AGI infrastructure platform B.AI announced that the Zhipu GLM-5.3-Flash (320B-A18B) officially launched on the platform and is fully open for free in the API official group. As the first native multimodal model in the GLM-5 series, GLM-5.3-Flash features a total of 320 billion parameters and 18 billion active parameters, supported by computing power from purely domestic AI chips. It introduces a mixed architecture of sparse and linear attention for the first time, combined with a 1M ultra-long context, offering both powerful performance and exceptional cost-effectiveness. Starting today, developers can call it at zero cost through the B.AI API official group, easily handling complex reasoning, long text processing, and multimodal tasks.

Zhipu officially announced the launch and open-sourcing of GLM-5.3-Flash, which is the first native multimodal model in the GLM-5 series.It is reported that the overall performance of GLM-5.3-Flash exceeds that of GLM-5.2, with programming and Agent evaluations approaching Claude Opus 4.8, but at only one-tenth the price of GLM-5.2. It also features a new foundational model, introducing a mixed architecture of sparse attention and linear attention for the first time in the main GLM series, and is pre-trained with 30T Token multimodal data.Zhipu stated that to gather extensive and professional feedback from a wide range of users, large-scale testing was conducted with the anonymous model Ox-Alpha (referred to as "Niu Lai" in the Chinese community) on OpenCode and OpenRouter before the official release. Ox-Alpha quickly became the most popular model of the week, setting a new high for call volume on both platforms, with all request traffic supported by domestic chip computing power.Previously, the community's DeepSWE small sample test for Ox Alpha once achieved 80%, but that was based on only 10 questions. After expanding the sample, the score fell back to about 63%, and testers also actively corrected the initial claim. This score still belongs to the top tier, but is not as exaggerated as the initial 80%. After the weights are open-sourced, developers can directly deploy using frameworks like vLLM, SGLang, KTransformers, without needing to go through the anonymous model's API.