DeepSeek: DeepSeek V4 Flash 0423

DeepSeek V4 Flash 0423 is an efficiency-optimized Mixture-of-Experts text model from DeepSeek, available on api14 under the model id deepseek/deepseek-v4-flash. It has 284B total parameters with 13B activated parameters, and it is built for fast inference. The provider release date for this version is 2026-04-24.

The model works on text only. It accepts text input and returns text output, so it does not take images, audio or files. Its context window is 1,048,576 tokens, which is roughly one million tokens, enough to keep very large documents or long conversations in a single request. The maximum output length is 943,718 tokens, so responses can themselves be very long. Because it is a Mixture-of-Experts design, only part of the parameters activate per token, which suits workloads where throughput matters alongside a large context.

The combination of long context and long output shapes the practical uses. It fits analysis and summarization of entire codebases, book-length documents or multi-hour transcripts in one pass, and it can draft lengthy outputs such as reports, specifications or documentation without splitting work across calls. The long context also supports retrieval-style setups where many source chunks are placed in the prompt, and long-running chat or agent loops that need to retain history. Because it is tuned for fast inference, it is a reasonable default for high-volume text tasks such as classification, extraction and bulk generation.

You call it through api14's OpenAI-compatible API using the model id deepseek/deepseek-v4-flash, which means existing OpenAI SDKs and clients work with a changed base URL and key. The model supports many request parameters, including temperature, top_p, top_k, min_p, top_a, frequency_penalty, presence_penalty and repetition_penalty for sampling control. You can cap or shape output with max_tokens, max_completion_tokens, stop and seed, and steer token-level behavior with logit_bias, logprobs and top_logprobs. For structured work it supports response_format and structured_outputs, and for agents it supports tools and tool_choice. Reasoning can be managed with reasoning, reasoning_effort and include_reasoning.

Since the model is text-only, a vision or audio model is a better fit when the input is not text. If you need a smaller or faster option for simple tasks, or a different provider's model, those are also worth comparing on the price table. Otherwise, for long-context text work in a single request, deepseek/deepseek-v4-flash is a straightforward choice through the OpenAI-compatible endpoint.