DeepSeek
DeepSeek V4.1 Flash combines text and vision with thinking controls, long context, and peak/off-peak direct API pricing.
At a glance
API model ID: deepseek-flash
Capabilities & boundaries
Tool support requires the appropriate API integration; a supported tool is not automatically active in every chat.
Thinking is on by default. For OpenAI-format requests, use thinking.type enabled/disabled and reasoning_effort. The effective levels are low, high and max: minimal maps to low; medium and xhigh map to high; ultra maps to max. Compare quality and latency on your own task before increasing effort.
Put it to work
Original examples from EZ Ai Assist. Adapt these to your task and the features available in your workspace.
Workflow 01
Turn visible evidence into a short, testable review.
Compare this screenshot with the requirements I provide. List visible mismatches, cite the relevant requirement, and describe a small test for each finding. Separate what the image proves from what would need an interactive check. Finish with the three most useful changes; do not assume hidden screens or behavior.
Workflow 02
Keep a long document task tied to quoted evidence.
Read the project documents below and create a decision log with decision, owner if stated, supporting section, unresolved question and next verification step. Mark missing values as not stated. Do not turn proposals into approved decisions. End with any contradictions that a project owner should resolve.
Workflow 03
Prepare a repeatable quality and latency comparison.
Using these representative tasks and acceptance criteria, design a small evaluation for low, high and max reasoning effort. Define a scoring rubric, failure categories and a results table for measured latency, token use and correctness. Do not invent results or prices. Recommend how we should choose the least expensive setting that passes.
Developer reference
These are DeepSeek direct API reference prices, not EZ Ai Assist subscription prices.
View EZ Ai Assist plans| Token type | Off-peak | Peak |
|---|---|---|
| Input · cache miss | $0.15 | $0.30 |
| Input · cache hit | $0.003 | $0.006 |
| Output | $0.60 | $1.20 |
Common questions
DeepSeek's current model table identifies deepseek-flash as DeepSeek V4.1 Flash. Older V4 Flash IDs can route to newer weights, so record the provider and resolved version when reproducibility matters.
The release and current pricing table document vision input. Ask for observations grounded in the supplied image, and verify interaction claims separately. Image input is not image generation.
Yes, the direct API supports enabled and disabled thinking. Thinking defaults to high effort; low, high and max are the distinct mapped levels. Availability of these controls in EZ Ai Assist must be checked in the app.
Outside the published weekday UTC peak windows, including weekends and Chinese public holidays. Use UTC when scheduling and check the provider's current table rather than assuming your local evening is off-peak.
No. Organize the input, identify the relevant sections and ask for evidence references. Evaluate retrieval and answer quality on your own documents instead of treating the maximum context size as a quality guarantee.
DeepSeek requires prior reasoning_content to be returned when requests carry tools, even for turns without a tool call. Follow its thinking-mode documentation and inspect the error before retrying.
No. The table is a developer reference for DeepSeek's direct API. Your EZ Ai Assist subscription, available models and exposed controls are separate; use the pricing page and app for those details.
Check the source
Specifications and API prices checked on . Example prompts and workflow advice are editorial guidance from EZ Ai Assist.
Same provider