Using DeepSeek V4.1 Flash 1017 on DeepInfra
Implementation guide · DeepSeek V4.1 · DeepSeek
DeepInfra exposes DeepSeek V4.1 Flash 1017 through model ID deepseek-ai/DeepSeek-V4.1-Flash-1017. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-10-17. Next refresh: weekly.
Quick Start
- 1
- 2Use the DeepInfra SDK or REST API to call
deepseek-ai/DeepSeek-V4.1-Flash-1017— see the documentation for request format. - 3
Code Examples
pip install openaiDEEPINFRA_API_KEYdeepseek-ai/DeepSeek-V4.1-Flash-1017DeepInfra uses "organization/model-name" format, e.g. "meta-llama/Meta-Llama-3-8B-Instruct" or "mistralai/Mistral-7B-Instruct-v0.3". See the DeepInfra model catalog for exact IDs.
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],
base_url="https://api.deepinfra.com/v1/openai"
)
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V4.1-Flash-1017",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on DeepInfra
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.60 |
| Image input | $1.00 |
Capabilities
About DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 is the October 17, 2026 update to DeepSeek V4.1 Flash, released under the MIT license with weights on Hugging Face and ModelScope. DeepSeek describes it as a minor update trained with reinforcement learning from self-feedback for end-to-end project development, with shorter task runtime and output length. It supports 1M-token context, up to 384K output tokens, vision input, thinking and non-thinking modes, tool calls and JSON output. The DeepSeek API serves it as deepseek-flash, and the legacy names deepseek-v4-flash and deepseek-v4-flash-vision-exp also route to it.