DeepSeek V4.1 Flash
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DeepSeek V4.1 Flash

deepseek-v4.1-flashllms.txt
DeepSeek
New
DeepSeek's latest model, DeepSeek V4.1 Flash, is in a mid-release internal beta and open for trial. It uses a new model architecture with native multimodal support, greater capability, faster speed, and lower cost. Because the model is still in internal testing, it will be rate-limited and is available only for testing—not recommended for production use.

Pricing

PricingWeb SearchCache Read
$0.142$0.284
$0.00056/request$0.0284/M tokens

Input Modalities

  • Text
  • Vision

Output Modalities

  • Text

Capabilities

  • Thinking
  • Tools
  • Tool calling
  • Structured outputs

Providers

DeepSeek deep-deepseek-v4.1-flash-expires-on-0910
Pricing$0.142$0.284
Web Search$0.00056/request
Cache Read$0.0284/M tokens
Context1M
Max output384K
Latency0.8S
Throughput162.5TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
100.00% uptime today

Performance for deepseek-v4.1-flash

Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

Uptime
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Latency
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Throughput
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Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://aihubmix.com/v1",
)

response = client.chat.completions.create(
    model="deepseek-v4.1-flash",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

print(response.choices[0].message.content)

Frequently asked questions

What is DeepSeek V4.1 Flash?

DeepSeek's latest model, DeepSeek V4.1 Flash, is in a mid-release internal beta and open for trial. It uses a new model architecture with native multimodal support, greater capability, faster speed, and lower cost. Because the model is still in internal testing, it will be rate-limited and is available only for testing—not recommended for production use.