AIREITER
QwenText Chat

Qwen3.8 Flash

Qwen3.8 Flash is a fast model for coding, agents, and long documents. 1M context. About $0.057 input and $0.193 output per million tokens.

InputOfficial $0.1143 per 1M tokensAIReiter $0.0571 per 1M tokensOutputOfficial $0.3857 per 1M tokensAIReiter $0.1929 per 1M tokensCache readOfficial $0.0143 per 1M tokensAIReiter $0.0071 per 1M tokensCache creationOfficial $0.1429 per 1M tokensAIReiter $0.0714 per 1M tokens
Run with API

INPUT

OUTPUT

Example
Generated in
42.7 seconds
Input tokens
134
Output tokens
2354
Tokens per second
55.13 tokens / second
Time to first token
-

Model details

Use the same model key in Playground, API requests, and internal workflows.

Model ID
qwen3.8-flash
Provider
Qwen
Protocol
OpenAI Chat Completions
Context window
1,000,000 tokens
Max output
131,072 tokens
Input tokens
5.7143 credits / 1M tokens
Output tokens
19.2857 credits / 1M tokens
Cache read
0.7143 credits / 1M tokens
Cache write
7.1429 credits / 1M tokens

A fast Qwen model for coding and long work

Qwen3.8 Flash is Alibaba's speed tier of Qwen3.8. It is built for coding, tool-using agents, and documents that do not fit in a short chat.

Big model, small cost

125 billion parameters in total, with about 6 billion used on each token. That is why it stays fast and cheap enough for high-volume work.

1 million tokens of context

Put a long spec, a pile of files, or a long agent trace in one request. A single reply can run up to 131,072 tokens.

Reads images as well as text

The model understands screenshots, charts, and documents, not just plain text. Use it when the task starts from something on screen.

About $0.057 / $0.193

Per million tokens, input is about $0.057 and output is about $0.193, roughly half the official list. Cached input is cheaper. The price bar above is the live rate.

Where Qwen3.8 Flash is strong

Qwen's own model card, published with the August 2026 release, scores Flash highest on coding and tool use among the models they compared.

Repository work

SWE-bench Pro 62.5. SWE-bench Multilingual 81.0. Use it to find a bug, edit several files, and check the result.

Agents that call tools

DeepSWE 58.7. Toolathlon 73.5. It holds a multi-step loop: read the failure, call a tool, and try again.

Code and hard questions

LiveCodeBench v6 is 91.9. GPQA Diamond is 91.7. Competitive programming and science questions are in range.

Looking at a screen

OSWorld partial score 52.3. MathVision 90.6, or 95.7 when it can run code. Screenshots and charts can go in with the question.

Flash or Max

Flash is the one you leave running all day. Max is the flagship when the job is harder than the budget.
01

Choose Flash

Coding agents, test-and-fix loops, long documents, and any workload where you care about the bill. The 1M window covers a long trace without splitting it up.

02

Choose Max

Qwen3.8 Max is the 2.4 trillion flagship. Use it when you want the strongest Qwen and the token price is secondary. Open it at /chat/qwen3-8-max.

03

Same request shape

Both models take a normal chat completion. For Flash, set the model to qwen3.8-flash. Raise max tokens when the answer needs a long trace. The default is 8,192 and the ceiling is 131,072.

Questions

Context, price, images, and how it compares with Max.

/ 01

What is Qwen3.8 Flash for?

Fast coding, tool-using agents, and long documents. It is the cheaper, quicker Qwen3.8, not a smaller copy of Max.

/ 02

How long is the context?

1 million tokens. One reply can be up to 131,072 tokens.

/ 03

How much does it cost?

About $0.057 input and $0.193 output per million tokens, about half the official list. Reading from cache costs less. There is no extra fee per tool call. The price bar is the live rate.

/ 04

Can it read images?

Yes. Screenshots, charts, and document images are part of the model, along with text.

/ 05

When should I use Qwen3.8 Max instead?

When you want the flagship and can pay more per token. Max is the 2.4T model. Flash is the one for volume.