DeepSeek V4.1 Flash
deepseek-v4.1-flashCompare deepseek-v4.1-flash API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 1M
- Maximum input window
- Max output
- 393.2K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
DeepSeek tokenizer (BPE)Performance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·DeepSeek V4.1 Flash
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About DeepSeek V4.1 Flash
从文本推理走向视觉协作
DeepSeek V4.1 Flash 可以结合文字与图片进行分析，适合编程助手、终端工作流和计算机使用智能体。它能围绕代码、日志与界面截图理解一个问题，让视觉信息参与后续判断，而不是把截图内容与文本任务分开处理。
适合需要多次观察和行动的工作
例如排查一个后台页面，可以先读取错误日志，再对照截图判断用户实际看到的状态，随后修改代码并检查结果。长流程任务则可以保留项目材料、关键约束与阶段成果，让模型持续推进到有明确完成标志的结果。应用提供终端、浏览器或其他工具后，这些分析才能转成实际操作。
图像理解适合界面分析、图表解读和视觉信息提取。输入截图时，应保留必要的上下文，并说明希望发现的问题；文字很小或画面不完整时，补充局部清晰截图比要求模型猜测更有效。
长任务也需要明确边界
V4.1 Flash支持思考与非思考模式，也支持JSON输出和工具调用。可以按任务选择相应方式：格式化提取重在字段稳定，复杂排障重在证据链与验证。多步骤执行中要保留失败信息和中间结果，并设置阶段检查点，避免模型在缺少实际状态时继续推测。
Use cases and prompting
视觉排障示例
“这是后台保存设置后的截图、浏览器报错和对应组件代码。请先说明界面状态与日志能共同证明什么，再沿提交与回显流程定位问题。提出最小修复，并验证保存失败、重复提交和刷新后回显三种情况。”
需要实际修改与测试时，让应用提供相关文件和执行工具。
截图里能看见信息，为什么仍会识别错？
小字、压缩和遮挡会影响判断。提供原尺寸或局部放大的清晰截图，并说明要关注的区域。
怎样让多步骤任务有明确结束？
事先写出完成条件，例如测试通过、页面回显正确、输出文件可打开；每一步根据实际结果检查，而不是只确认计划已写完。
API access
API documentation
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| official | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about deepseek-v4.1-flash
What is deepseek-v4.1-flash?
Compare deepseek-v4.1-flash API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call deepseek-v4.1-flash?
Create an API key with access to deepseek-v4.1-flash, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is deepseek-v4.1-flash priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of deepseek-v4.1-flash?
The model catalog lists a context window of 1048576 tokens. Check the selected endpoint for request limits.
What is the maximum output of deepseek-v4.1-flash?
The model catalog lists a maximum output of 393216 tokens. Your request settings may set a lower limit.
How should I evaluate deepseek-v4.1-flash for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.