Qwen3.8 Flash
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Qwen3.8 Flash

qwen3.8-flashllms.txt
Qwen
Qwen3.8 Flash is Alibaba Cloud Qwen’s flagship native vision-language model for coding, office tasks, long-context reasoning, and agent workflows. It supports a 1M-token context, 128K output, web access, and tool calling. Compared with Qwen3.7-Plus, Qwen3.8-Flash significantly reduces training and inference costs—the training overhead is only about one-ninth of the former—while offering stronger capabilities on coding and office tasks.

Pricing

PricingWeb SearchCache WriteCache Read
$0.142$0.426
$0.000548/request$0.1775/M tokens$0.0142/M tokens

Input Modalities

  • Text

Output Modalities

  • Text

Capabilities

  • Thinking
  • Web
  • Tools
  • Tool calling
  • Structured outputs
  • Long context

Providers

Alibaba Cloud alicloud-qwen3.8-flash
Pricing$0.142$0.426
Web Search$0.000548/request
Cache Write$0.1775/M tokens
Cache Read$0.0142/M tokens
Context1M
Max output128K
Latency12.4S
Throughput29.8TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
100.00% uptime today

Performance for qwen3.8-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="qwen3.8-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 Qwen3.8 Flash?

Qwen3.8 Flash is Alibaba Cloud Qwen’s flagship native vision-language model for coding, office tasks, long-context reasoning, and agent workflows. It supports a 1M-token context, 128K output, web access, and tool calling. Compared with Qwen3.7-Plus, Qwen3.8-Flash significantly reduces training and inference costs—the training overhead is only about one-ninth of the former—while offering stronger capabilities on coding and office tasks.