DeepSeek V4.1 Flash 1017 on DeepInfra

DeepSeek V4.1 · DeepSeek

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Last refreshed 2026-10-17. Next refresh: weekly.

Why use DeepSeek V4.1 Flash 1017 on DeepInfra?

DeepInfra offers DeepSeek V4.1 Flash 1017 with pay-as-you-go pricing at $0.20/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.

Compare DeepSeek V4.1 Flash 1017 across 4 providers to find the best fit for your use case
Input / 1M
$0.20
Output / 1M
$0.60
Cache
read $0.006
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export DEEPINFRA_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
Model ID
deepseek-ai/DeepSeek-V4.1-Flash-1017

Request example

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)

Gotchas

  • Use provider model ID "deepseek-ai/DeepSeek-V4.1-Flash-1017", not the LLMReference slug "deepseek-v4.1-flash-1017".
  • DeepInfra 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.
  • The examples expect DEEPINFRA_API_KEY; rename it only if your application config maps the new variable.

Compare DeepSeek V4.1 Flash 1017 Across Providers

ProviderInput (per 1M)Output (per 1M)
DeepSeek Platform$0.30$1.20
Vercel AI Gateway$0.30$1.20
OpenRouter$0.30$1.20
DeepInfra$0.20$0.60

Pricing

TypePrice (per 1M)
Input tokens$0.20
Output tokens$0.60
Image input$1.00

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsPrompt Caching

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.

Get Started

Model Specs

Released2026-10-17
Parameters552B
Context1M
ArchitectureMixture of Experts