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Stepfun AI has launched Step 3.7 Flash, a 198B sparse Mixture-of-Experts vision-language model optimized for high-speed agentic coding and browser automation.

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Stepfun AI has launched Step 3.7 Flash, a 198B sparse Mixture-of-Experts vision-language model optimized for high-speed agentic coding and browser automation.
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// 1h agoMODEL RELEASE

Stepfun AI has launched Step 3.7 Flash, a 198B sparse Mixture-of-Experts vision-language model optimized for high-speed agentic coding and browser automation.

Stepfun AI has released Step 3.7 Flash, a highly efficient 198B-parameter sparse Mixture-of-Experts (MoE) vision-language model designed specifically for real-world agentic workflows like browser automation and coding. Activating just 11B parameters per token to achieve blazing-fast speeds of up to 400 tokens per second, the model supports a massive 256K context window and native multimodal capabilities, allowing it to process text, GUIs, and wireframes. Released under the Apache 2.0 license, it is available for local deployment and via platforms like OpenRouter, featuring unique selectable reasoning levels (low, medium, high) that give developers granular control over speed, cost, and analytical depth.

// ANALYSIS

Offering selectable reasoning levels in an open-weight, high-speed MoE vision-language model is a major breakthrough for agentic applications, enabling developers to build cost-effective architectures where deep thinking is dynamically engaged only when needed.

* Extreme high throughput of up to 400 tokens per second is a perfect match for real-time agentic tool use and iterative browser tasks.

* Three selectable reasoning modes (low, medium, high) allow developers to customize execution speed and cost to match the specific complexity of a subtask.

* Open-weight release under Apache 2.0 invites wide integration, though the 198B total parameter count still requires high-end hardware with 128GB+ unified memory for local runs.

* Native multimodal and GUI design makes it exceptionally capable of parsing complex wireframes, UI layouts, and charts without requiring extra visual-indexing pipelines.

// TAGS
step-3.7-flashstepfunmoevision-languageopen-sourceagentmachine-learningdeep-learning

DISCOVERED

1h ago

2026-06-01

PUBLISHED

1h ago

2026-06-01

RELEVANCE

9/ 10

AUTHOR

Bijan Bowen