Last refreshed 2026-10-19. Next refresh: weekly.
Why use DeepSeek V4.1 Flash 1017 on Together AI?
Together AI offers DeepSeek V4.1 Flash 1017 with pay-as-you-go pricing at $0.30/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Compare DeepSeek V4.1 Flash 1017 across 6 providers to find the best fit for your use caseSetup recipe
Python + curlpip install togetherexport TOGETHER_API_KEY=...from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V4.1-Flash-1017",deepseek-ai/DeepSeek-V4.1-Flash-1017Request example
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
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".
- Together uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
- The examples expect TOGETHER_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 |
| Together AI | $0.30 | $1.20 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $1.20 |
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.