DeepSeek V3.1: Entering the Agent Era with Hybrid Inference
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DeepSeek has announced the release of DeepSeek-V3.1, presenting it as its first step into what the company calls the “agent era.” The update builds on the earlier V3 model while focusing on efficiency, long-context handling, and stronger agent-style capabilities.
Hybrid Inference: Two in One
DeepSeek-V3.1 introduces a dual-mode design:
Users can toggle between these modes through the new “DeepThink” button, tailoring the model’s behavior to different task needs.
Performance and Agent Skills
According to the release, DeepSeek-V3.1-Think delivers answers faster than its predecessor DeepSeek-R1-0528. Post-training improvements are also highlighted, with the model showing stronger tool-use capabilities and greater ability to complete multi-step agent tasks.
The company reports better benchmark results, including improved scores on SWE and Terminal-Bench, and more efficient reasoning in complex search tasks.
API and Developer Updates
Developers gain access to two API endpoints:
Model and Open-Source Availability
DeepSeek states that V3.1 builds on 840 billion tokens of continued pretraining for long-context extension. Updates include a new tokenizer and chat template.
For researchers and developers, open-source weights are available on Hugging Face:
While DeepSeek is a relatively new player in a field already populated by established names, V3.1 represents a clear move toward positioning itself in the AI agent landscape. With hybrid inference, extended context, and open-source availability, the release gives both users and developers an opportunity to experiment with agent-oriented workflows.
About the Author
Ryan Chen
Ryan Chan is an AI correspondent from Chain.
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