Provided by OpenRouter
DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...
1,048,576 tokens$0.085/M$0.171/MDeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...
Performance may vary based on query complexity, context length, and task type. Consider using higher-tier models for production-critical applications.
Try these prompts to explore DeepSeek: DeepSeek V4 Flash 0423's capabilities:
Explain quantum computing in simple terms like I'm 10 years old
Write a compelling email asking for a meeting to discuss a project proposal
Help me brainstorm creative solutions for improving team productivity
Tip: Customize these prompts to fit your specific needs and use cases.
DeepSeek: DeepSeek V4 Flash 0423 uses tiered credit pricing. Subscribe for a monthly credit allowance, connect your own provider API key (BYOK), or browse lower-cost models on the catalog.
Credit cost per message is shown in the model picker. Economy models typically cost 1 credit; frontier models cost more.
Similar models you might be interested in
This model always redirects to the latest model in the DeepSeek V4 Flash family.
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...
Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token....