SambaNova Deploys Zhipu's GLM-5.3 on SambaCloud, Claims Inference Speed Exceeds 200 Tokens/s
SambaNova announced that Zhipu's latest open-source model, GLM-5.3, is now supported on its cloud platform, showcasing high throughput and caching efficiency data for long-horizon coding agents.
AI chip and cloud service provider SambaNova announced on November 11, 2026, that Zhipu AI's flagship open-weight model, GLM-5.3, is now running on its inference cloud platform, SambaCloud. Designed for complex software engineering and long-horizon agent tasks, the model achieves state-of-the-art results among open-weight models on benchmarks like Terminal-Bench 3.0 and DeepSWE v1.1, while using fewer output tokens per task than several closed frontier models, according to SambaNova.
To demonstrate real-world performance, SambaNova provided a trace from a typical agent run: over 17 minutes and 30 seconds, the model made 41 calls, processing 5.4 million input tokens but generating only about 42,000 output tokens. Because each step in an agent loop re-sends all previously seen context, input tokens grew from 38K on the first call to over 114K by the eighth. SambaNova noted that more than 91% of this input was served from cache, keeping per-call latency low enough for developers to complete entire tasks in real-time interaction.
Currently, GLM-5.3 runs at over 200 tokens/s on SambaCloud. This high throughput makes it suitable for production agent workflows that require frequent tool calls and fast feedback.