Last refreshed 2026-10-17. Next refresh: weekly.
Why use DeepSeek V4.1 Flash 1017 on Vercel AI Gateway?
Vercel AI Gateway offers DeepSeek V4.1 Flash 1017 with pay-as-you-go pricing at $0.30/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.
Compare DeepSeek V4.1 Flash 1017 across 4 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport AI_GATEWAY_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],deepseek/deepseek-v4.1-flash-1017Request example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="deepseek/deepseek-v4.1-flash-1017",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "deepseek/deepseek-v4.1-flash-1017", not the LLMReference slug "deepseek-v4.1-flash-1017".
- creator/model-name e.g. kwaipilot/kat-coder-pro-v2
- The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.
Compare DeepSeek V4.1 Flash 1017 Across Providers
| Provider | Input (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
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $1.20 |
| 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.