DeepSeek V4.1 Flash
对 比
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DeepSeek V4.1 Flash

deepseek-v4.1-flashllms.txt
DeepSeek
DeepSeek-V4.1-Flash model official release. This is the smallest model in DeepSeek’s new model-architecture series, featuring native multimodal visual understanding capabilities. The new architecture is designed to deliver a higher capability ceiling, faster inference speeds, greater throughput, and scalability to larger-parameter models.

定价

TierPricingCache Read
空閒時段 · 04:00–06:00, 10:00–01:00 UTC
$0.155$0.62
$0.0031/M tokens
高峰時段 · 01:00–04:00, 06:00–10:00 UTC
$0.3098$1.2392
$0.0062/M tokens

輸入模式

  • Text
  • Vision

輸出模式

  • Text

上下文

  • 1M tokens

最大輸出

  • 384K tokens

能力

  • Thinking
  • Streaming
  • Tool calling
  • Web search
  • URL context
  • Code interpreter
  • Computer use
  • File search
  • Memory tool
  • Structured outputs
  • Structured decision
  • Citations
  • Prompt caching
  • Background mode
  • Server-side sessions

供應商

Bytedance doubao-deepseek-v4.1-flash
空閒時段04:00–06:00, 10:00–01:00 UTC
Pricing$0.1408$0.5632
Cache Storage$0.0024/h/M tokens
Cache Read$0.0028/M tokens
Web Search$0.0031/request
高峰時段01:00–04:00, 06:00–10:00 UTC
Pricing$0.2816$1.1264
Cache Storage$0.0024/h/M tokens
Cache Read$0.0056/M tokens
Web Search$0.0031/request
PrecisionⓘNot Disclosed
Latency5.8S
Throughput66.9TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Baidu baidu-deepseek-v4.1-flash
空閒時段14:00–00:00 UTC
Pricing$0.1408$0.5632
Cache Read$0.0028/M tokens
高峰時段00:00–14:00 UTC
Pricing$0.2816$1.1264
Cache Read$0.0056/M tokens
PrecisionⓘNot Disclosed
Latency3.3S
Throughput77.3TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Tencent tencent-deepseek-v4.1-flash
空閒時段04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
高峰時段01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘNot Disclosed
Latency1.9S
Throughput8.1TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Pareto pareto-deepseek-v4.1-flash
空閒時段04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
Web Search$0.00077/request
高峰時段01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
Web Search$0.00077/request
PrecisionⓘNot Disclosed
Latency1.7S
Throughput11.4TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
100.00% uptime today
Alibaba Cloud alicloud-deepseek-v4.1-flash
空閒時段14:00–00:00 UTC
Pricing$0.1408$0.5632
Cache Read$0.0141/M tokens
Web Search$0.00062/request
高峰時段00:00–14:00 UTC
Pricing$0.2816$1.1264
Cache Read$0.0282/M tokens
Web Search$0.00062/request
PrecisionⓘNot Disclosed
Latency0.9S
Throughput16.9TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Morph morph-deepseek-v4.1-flash
空閒時段04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
高峰時段01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘNot Disclosed
Latency0.8S
Throughput16.8TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Azure azure-deepseek-v4.1-flash
Pricing$0.3$1.2
Cache$0.006
PrecisionⓘNot Disclosed
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Deepinfra deepinfra-deepseek-v4.1-flash
空閒時段04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
高峰時段01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘFP8
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Atlas atlas-deepseek-v4.1-flash
Pricing$0.3$1.2
Cache$0.03
PrecisionⓘNot Disclosed
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today

性能对比 deepseek-v4.1-flash

Uptime 指過去 72 小時內請求成功的百分比。AIHubMix 持續監控每個供應商,當某個供應商回傳錯誤或回應過慢時,會自動切換到次佳供應商重試;Latency 指請求的總往返耗時(越低越好);Throughput 指模型的輸出速度(每秒 token 數,越高越好)。

Uptime
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快速开始

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-V4.1-Flash model official release. This is the smallest model in DeepSeek’s new model-architecture series, featuring native multimodal visual understanding capabilities. The new architecture is designed to deliver a higher capability ceiling, faster inference speeds, greater throughput, and scalability to larger-parameter models.