Updated September 10, 2026: DeepSeek V4.1 Flash is released. Use
deepseek-flash. The old Flash aliases now route to this version;deepseek-v4-prois scheduled to switch on September 14 at 04:00 UTC. Direct DeepSeek API usage has separate billing.
The current model names
DeepSeek released V4.1 Flash on September 10. Its API identifier is deepseek-flash; this is the recommended name for new integrations. The legacy deepseek-v4-flash and deepseek-v4-flash-vision-exp identifiers remain accepted and now route to V4.1 Flash.
On September 10, deepseek-v4-pro still identifies V4 Pro. The provider has announced that this alias will route to V4.1 Flash from September 14, 2026 at 04:00 UTC. Treat that as a scheduled change, not a change already verified as complete. Record the actual model metadata and date with each run.
Use it in MonkeyCode
MonkeyCode includes DeepSeek V4.1 Flash with free access under your current account terms. Start a task without setting up a separate DeepSeek API integration. Direct API requests to DeepSeek are a separate service and follow the provider’s pricing. A free MonkeyCode entry does not mean the official DeepSeek API is free.
Check compatibility before switching an agent
Start with one text request using the developer example. Then check one tool call, a multi-turn continuation and error handling independently. A compatible request format does not prove identical tool behavior or persistent conversation state. DeepSeek has a Responses API guide; its compatibility table explicitly marks some fields and tools as unsupported or ignored.
Budget from a completed change
This guide deliberately does not reuse July dollar prices, peak-hour multipliers or a Pro/Flash price ratio. Open the current pricing link from the official API documentation when budgeting; keep the currency, cache category, model and check date with the quote. Count retries, tool execution, compute and reviewer corrections in addition to token usage.
Use the first-task exercise to compare an accepted result on your own setup. A vendor benchmark and a small local exercise answer different questions; neither establishes production performance for your repository.