Model intelligence / Live profile
GLM-5.3-Flash
Track GLM-5.3-Flash across launches, availability, pricing, benchmarks, capabilities, and consequential updates. This page updates automatically as substantive Superpower Daily coverage is published.
Coverage telemetryActive
Entity type
AI modelPublished4
Launches2
Pricing0
Benchmarks0
Published coverage4 stories
Last 90 days4 updates
Coverage dates3 days
Profile statusIndexed
ReleaseGLM-5.3-Flash
AvailabilityZ.ai API; weights available on Hugging Face
Context1M
Input / 1M$0.15
Output / 1M$0.5
Latest coverage
What changed around GLM-5.3-Flash.
Durable signals
Launches, pricing, and proof.
012 records
Launches and releases
020 records
Pricing and access
No material pricing update yet.
030 records
Benchmarks and evaluations
No substantive benchmark coverage yet.
Update timeline
The maintained record.
Enterprise adoptionModel-Serving Platforms Reach 6.1% of AI-Spending Businesses, While Frontier Spend HoldsThe early shift is showing up in specialized deployments and model-serving platforms, while direct business spending still favors Anthropic and OpenAI.LaunchZ.ai Says 100,000 Chinese Chips Serve GLM-5.3-Flash; Shares Rise More Than 8%The low-cost model is a test of whether China-made hardware can support a public AI service at scale, but Z.ai has not named the chipmakers behind the system.Model launchesZ.ai releases GLM-5.3-FlashZ.ai released GLM-5.3-Flash with open weights, MIT licensing, a one-million-token context window, and API availability. The model is positioned as a lower-cost alternative to GLM-5.3 and was reportedly served on Chinese AI chips.Model launchesZhipu AI releases GLM-5.3-FlashZhipu AI released GLM-5.3-Flash, an open-source MIT-licensed native multimodal model with a 1-million-token context window and 300 billion parameters. The company says it is served by more than 100,000 domestically produced chips.Open releaseZ.ai Releases 320B GLM-5.3-Flash With MIT Weights, 1M Context and Low API RatesThe model gives developers a permissively licensed route to long-context, image and video workloads, while its performance and serving-efficiency claims remain company-reported results.
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