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Qwen3.8 Max 0902

alibaba·alibaba/qwen3.8-max-0902·GA·Closed·qwen3.8-max series·NEW
Qwen3.8 Max 0902 is Alibaba's September 2 checkpoint of its flagship Qwen3.8 Max model for coding, knowledge work, data analysis, and long-running agent workflows. It supports text, image, video, PDF input, selectable thinking, tool calling, structured output, and a near-million-token context window.

Qwen3.8 Max 0902 by alibaba is currently listed from a single provider. Its reference price is $2.00 per 1M input tokens and $6.00 per 1M output tokens.

The context window is 991,808 tokens, with an output limit of 131,072 tokens. It supports reasoning, tool use, and structured output. Accepted input modalities are Text, Image, Video, and PDF.

Specs & pricing

Input / output per 1M tokens
Reference price·NanoGPT
$2.00 / $6.00
Blended $3.00 · Cache read $0.17
Lowest paid·NanoGPTGateway
$2.00 / $6.00
Blended $3.00
Context
991,808
Output limit
131,072
Knowledge cutoff
—
Released / updated
2026-09-02 / 2026-09-02
Capabilities
✓ Reasoning✓ Tool use✓ Structured output? Temperature✓ Attachments
Modalities
TextImageVideoPDF

Available at 1 providers1 with public prices

ProviderTierInputOutputCache readCache writeContextOutput limitStatus
NanoGPTGateway$2.00$6.00$0.17$2.50991,808131,072

Sorted by blended price (input×0.75 + output×0.25) asc. The official channel always shows regardless of rank. Whether a gateway's low price is actually usable can't be verified.

Your usage cost

1NanoGPT$480.40
The cheapest paid channel is the only channel.

Reasoning control

effort = noneeffort = high

Related models

DeepSeek V4 Flashcheaper alternative$0.14 / $0.28DeepSeek V4 Procheaper alternative$0.435 / $0.87DeepSeek V4 Flash 0731cheaper alternative$0.445 / $1.34MiniMax-M3cheaper alternative$0.30 / $1.20

Price historyone sample accumulated per data sync

Input list $2.00Output list $6.00Min blended $3.00

Price history accumulates from each data sync; currently only 1 sample(s) (2026-09-02). Each future sync adds a point, and once accumulated a line is drawn here.

Data partly from models.dev (MIT) · NanoGPT official docs ↗