Strengths
- Very cheap: $0.15 input and $0.47 output per million tokens, with a one-million-token context.
- Only 6 billion active parameters, yet it accepts images and video. The hosted version has a one-million-token context by default and built-in tools.
- In Frankfurt you get it in EU scope, with processing kept inside the EU, at the same price as in Singapore.
- You can download the open preview, Qwen3.8-Flash-Next, and run it on your own server.
Weaknesses
- Benchmark results, including the comparison with Claude Opus 4.8, are Alibaba's own claims and were not independently reproduced at launch.
- On the hard HLE test the open preview scores 35.9, below Claude Opus 4.6 (40.0) in Alibaba's own table.
- The open preview uses the qwen-community-1.0 license, not a standard open-source one, so read it before you deploy.
Best for
- high volumes of cheap API tasks
- processing kept in the EU via Frankfurt
- extracting data from images and video
Not ideal for
- the hardest reasoning tasks
How to use it in Europe
Through the API in Alibaba Cloud Model Studio. In Frankfurt you get it in EU scope, where data is stored in Germany and processing stays inside the EU, at the same price as in Singapore. For companies dealing with GDPR it is the most suitable hosted Qwen. Global scope in Frankfurt is slightly cheaper but has no EU boundary. You can also download the open preview, Qwen3.8-Flash-Next, and run it on your own server.
Price compared with similar models
Benchmark results
| Benchmark | Score | Source |
|---|---|---|
| SWE-bench Pro (Qwen3.8-Flash-Next, vendor-reported) | 62.5 | huggingface.co ↗ (vendor-reported), August 2026 |
| GPQA Diamond (Qwen3.8-Flash-Next, vendor-reported) | 91.7 | huggingface.co ↗ (vendor-reported), August 2026 |
| LiveCodeBench v6 (Qwen3.8-Flash-Next, vendor-reported) | 91.9 | huggingface.co ↗ (vendor-reported), August 2026 |
Benchmarks cover only a narrow slice of ability and vendors often report them at their best settings. Treat them as a rough guide.
More models from this vendor
- Qwen3.8-Max: Alibaba's flagship with a one-million-token context that understands text, images and video. Strong at coding and fairly priced.
- Qwen3.7-Plus: An affordable mid-range Qwen model for everyday business tasks through the API, with a one-million-token context and image input.
- Qwen3.8-2.4T-A95B: The open-weight text base of Qwen3.8-Max with 2.4 trillion parameters, for large companies with their own GPU cluster.
- Qwen3.8-27B: A small open Qwen model under Apache 2.0 that runs on your own computer and understands images and video.
Similar models from other vendors
- Claude Haiku 5.5 (Anthropic): Claude's cheapest and fastest model, built for classification, data extraction and large volumes of simple tasks.
- DeepSeek V4.1 Flash (DeepSeek): DeepSeek's cheap, fast open-weight model with a 1 million token window. In the app and API, though, your data goes to China.
- Gemini 3.5 Flash-Lite (Google): A very fast, low-cost Google model for large volumes of simple tasks, such as pulling data out of documents.
- Mistral Small 4 (Mistral AI): Mistral's cheap, fast open model under Apache 2.0 for everyday tasks through the API or on your own server.
- GPT-6.1 Terra (OpenAI): OpenAI's fast, cheaper model for working with images, operating a computer and everyday office work.
- Grok 4.3 (xAI): An older, cheaper Grok from April 2026 with a 1-million-token window. Good for lots of low-cost API calls.