# deepseek-ai/DeepSeek-V4.1-Flash-1017

> OpenAI-compatible language or vision-language model

This file is intended for AI coding agents wiring an application to this specific Chutes model.

## Important URLs

- Model page: https://chutes.ai/app/chute/chutes-deepseek-ai-deepseek-v4-1-flash-1017
- Model llms.txt: https://chutes.ai/app/chute/chutes-deepseek-ai-deepseek-v4-1-flash-1017/llms.txt
- Model OpenAPI 3.1 spec (this chute, callable): https://chutes.ai/app/chute/chutes-deepseek-ai-deepseek-v4-1-flash-1017/openapi.json
- Global Chutes llms.txt: https://chutes.ai/llms.txt
- Full Chutes docs export: https://chutes.ai/llms-full.txt
- Management API OpenAPI (account/billing/keys, NOT this model): https://api.chutes.ai/openapi.json

## Model Identifiers

- Name: `deepseek-ai/DeepSeek-V4.1-Flash-1017`
- Chute ID: `34c7b79d-854b-5e32-981a-774d322062b0`
- Slug: `chutes-deepseek-ai-deepseek-v4-1-flash-1017`
- Owner: `chutes`

## Authentication

- Use `Authorization: Bearer $CHUTES_API_KEY` for inference calls.
- Send JSON request bodies with `Content-Type: application/json` unless the endpoint documentation says otherwise.
- The request body is FLAT — send the request fields at the top level (no `input_args`/`args` wrapper).
- This model is served on the shared OpenAI-compatible gateway. Set the request `model` field to the exact Name above (`deepseek-ai/DeepSeek-V4.1-Flash-1017`), and use base URL `https://llm.chutes.ai/v1`.
- For base64 media fields, send raw base64 strings in API requests. The web playground may use temporary Blob upload references internally for large files before proxying to Chutes.

## Pricing

- $0.30 input / $1.20 output per 1M tokens
- $0.03 cached input per 1M tokens
- Check the model page for current pricing.

## Endpoints

### 1. POST /v1/chat/completions

- Base URL: `https://llm.chutes.ai`
- Output content type: `application/json`

Request fields:

- No request schema is published for this endpoint.

Example call:

cURL:

```bash
curl -X POST "https://llm.chutes.ai/v1/chat/completions" \
  -H "Authorization: Bearer $CHUTES_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
  "messages": [
    {
      "role": "user",
      "content": "Hello!"
    }
  ],
  "stream": false,
  "max_tokens": 1024,
  "temperature": 0.7
}'
```

Python:

```python
import os
import requests

api_key = os.environ.get("CHUTES_API_KEY")
if not api_key:
    raise ValueError("Missing CHUTES_API_KEY")

url = "https://llm.chutes.ai/v1/chat/completions"
headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json",
}
data = {
    "model": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "messages": [
        {
            "role": "user",
            "content": "Hello!"
        }
    ],
    "stream": False,
    "max_tokens": 1024,
    "temperature": 0.7
}

response = requests.request("POST", url, headers=headers, json=data)
response.raise_for_status()

result = response.json()
print(result)
```

### 2. POST /v1/chat/completions

- Base URL: `https://llm.chutes.ai`
- Output content type: `application/json`
- Streaming: yes

Request fields:

- No request schema is published for this endpoint.

Example call:

cURL:

```bash
curl -X POST "https://llm.chutes.ai/v1/chat/completions" \
  -H "Authorization: Bearer $CHUTES_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
  "messages": [
    {
      "role": "user",
      "content": "Hello!"
    }
  ],
  "stream": true,
  "max_tokens": 1024,
  "temperature": 0.7
}'
```

Python:

```python
import os
import requests

api_key = os.environ.get("CHUTES_API_KEY")
if not api_key:
    raise ValueError("Missing CHUTES_API_KEY")

url = "https://llm.chutes.ai/v1/chat/completions"
headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json",
}
data = {
    "model": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "messages": [
        {
            "role": "user",
            "content": "Hello!"
        }
    ],
    "stream": True,
    "max_tokens": 1024,
    "temperature": 0.7
}

import json

response = requests.request("POST", url, headers=headers, json=data, stream=True)
response.raise_for_status()

for line in response.iter_lines():
    if not line:
        continue
    line = line.decode("utf-8")
    if not line.startswith("data: "):
        continue
    chunk = line[6:]
    if chunk == "[DONE]":
        break
    try:
        choices = json.loads(chunk).get("choices") or []
    except json.JSONDecodeError:
        continue
    if not choices:
        continue
    content = choices[0].get("delta", {}).get("content")
    if content:
        print(content, end="", flush=True)
print()
```

## Agent Integration Checklist

- Pick the endpoint path that matches the desired task.
- Set `CHUTES_API_KEY` in the server-side environment only.
- Validate required fields before sending requests.
- For media models, keep file upload, base64 conversion, and output preview/download handling explicit in the app UI.