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DeepSeek V4 Flash 0423 API

DeepSeek V4 Flash 0423 is a large language model by DeepSeek, available on the Venice API as deepseek-v4-flash. Private and end-to-end encrypted variants are available.DeepSeek V4 Flash is an efficiency-optimized 284B-parameter Mixture-of-Experts model with 13B active parameters and a 1M-token context window. Tuned for fast inference and high-throughput workloads while maintaining strong reasoning and coding performance.

DeepSeek V4 Flash 0423 API pricing

DeepSeek V4 Flash 0423 specifications

How to use the DeepSeek V4 Flash 0423 API

Send requests to POST https://api.venice.ai/api/v1/chat/completions with "model": "deepseek-v4-flash" and your API key.

DeepSeek V4 Flash 0423 API FAQ

How much does the DeepSeek V4 Flash 0423 API cost?

0.14per1Minputtokensand0.14 per 1M input tokens and 0.28 per 1M output tokens, with cached input at 0.028per1M.TheE2EEvariantcosts0.028 per 1M. The E2EE variant costs 0.18 input and $0.37 output. Prices are in USD and can be paid in DIEM at parity.

What is the DeepSeek V4 Flash 0423 model ID?

Use deepseek-v4-flash as the model parameter. Other variants: e2ee-deepseek-v4-flash (E2EE).

Is the DeepSeek V4 Flash 0423 API private?

The Standard variant is private: requests run on infrastructure Venice controls with zero data retention, and prompts and outputs are never stored or used for training. The E2EE variant is end-to-end encrypted: prompts are encrypted on your device and decrypted only inside an attested hardware enclave, so neither Venice nor the GPU provider can read them.

What is the context window of DeepSeek V4 Flash 0423?

1M tokens of context, with up to 32K output tokens per response.

What does DeepSeek V4 Flash 0423 support?

DeepSeek V4 Flash 0423 supports function calling, structured outputs, reasoning, web search and prompt caching. Reasoning effort is adjustable with reasoning_effort: none, low, medium and high (default low).

Which endpoint does the DeepSeek V4 Flash 0423 API use?

Call POST /chat/completions. /responses (Alpha) is also supported.

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