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GLM-5.3-Flash

GLM-5.3-Flash emerged in late August 2026 under the "Ox Alpha" label, with weights made available via an NVIDIA Developer Forums thread in the DGX Spark / GB10 Projects category. The release was notable for its unconventional launch: a free listing appeared on OpenRouter and OpenCode without an identified owner or model card, yet quickly climbed to become the platform's most-used model within roughly six days, processing about 23 trillion tokens and reportedly drawing around 2.3 times the volume of the next most-trafficked option. Community coverage framed this trajectory as evidence that a competitive multimodal system can scale outside traditional provider pipelines.

Beyond availability, the model's defining practical promise is local, single-machine inference. Third-party reporting describes GLM-5.3-Flash as an open multimodal system that runs on a single Mac, making it attractive for founders, independent builders, and small teams who want strong multimodal capability without cloud dependency. Its multimodal scope aligns it with broader text and image understanding tasks, and the focus on consumer-grade hardware suggests an intended use pattern of on-device assistants, prototyping, and privacy-sensitive workflows rather than large-scale cloud orchestration.

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Model key
glm5.3-flash
Release date
Aug 26, 2026
Last updated
Aug 26, 2026
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Latest news about GLM-5.3-Flash

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CoverageBenchmark

GLM-5.3-Flash is a sparse mixture-of-experts model from Z.ai with 320B total parameters and 18B active per token, released on August 26, 2026 in FP8 and BF16 checkpoints under an MIT license, with weights published on Hugging Face and API pricing set at $0.15 per million input tokens. According to the LumaDock explaine On Z.ai's launch table, GLM-5.3-Flash posts 63.4 Pass@1 on DeepSWE v1.1 (versus 46.2 for GLM-5.2), 84.3 on Terminal-Bench 2.1 (Claude Opus 4.8 at 85.0 and GPT-5.6 Terra at 87.4), and 55.3 on Humanity's Last Exam with tools, and Z.ai claims a hybrid linear-plus-sparse attention design that delivers roughly 3x less atten

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