Qwen3.8-Max — Specifications
Rédigé par Mustafa Ihsan d’après la documentation officielle du fournisseur · Dernière mise à jour
| Développeur | Alibaba |
|---|---|
| Type | LLM (architecture MoE, raisonnement, multimodal) |
| Modalité | Text, Image, Video → Text |
| Paramètres | 2.4T total (MoE) |
| Fenêtre de contexte | 1 million |
| Sortie maximale | 128 K |
| Licence | Proprietary (hosted) |
| Poids ouverts | Non |
| Publié | 2026-08 |
| Prix de l’entrée | $2.00 /1M |
| Prix de la sortie | $6.00 /1M |
| Fournisseurs d'API | Alibaba Cloud Model Studio, Qwen Cloud |
What is Qwen3.8-Max?
Qwen3.8-Max is Alibaba’s flagship Qwen model, launched on Alibaba Cloud Model Studio (International) on 2 August 2026. Alibaba le décrit as a 2.4-trillion-parameter mixture-of-experts with a major leap in coding and office productivity, built to handle professional tasks in law, finance and design, with native understanding of images and video. Qwen calls it the official version of its open-weight Qwen3.8-2.4T-A95B (2.4T total, 95B active parameters), with extra features such as vision input, a non-thinking mode, a 1M-token context by default and built-in tools. An upgraded snapshot, qwen3.8-max-0902, followed on 2 September 2026 at the same price.
In Model Studio’s US and International deployment scopes it costs $2.00 per million input tokens and $6.00 per million output tokens, with implicit cache hits at $0.25 per million. Model Studio’s Global deployment scope lists it at $1.65 / $4.951, and Qwen Cloud, the official Qwen API service, charges $2.00 / $6.00. The context window is 1,000,000 tokens, with up to 131,072 output tokens.
It succeeds the April 2025 Qwen3 generation at the top of Alibaba’s range; the open Qwen3 235B-A22B remains the self-hostable flagship of that family, with a 32K native context. For Alibaba’s smaller open-weight Qwen3.8 model, see Qwen3.8-27B. Background on the family is in our Qwen d’Alibaba expliqué guide, and the Calculateur de coûts pour les API IA estimates a monthly bill.
Qwen3.8-Max pricing: API cost per 1M tokens
| Entrée (par million de jetons) | $2.00 |
|---|---|
| Sortie (par million de jetons) | $6.00 |
| Ratio sortie/entrée | 3× |
| Moyenne pondérée (4:1 entrée:sortie) | $2.80 par 1 million de jetons |
What Qwen3.8-Max costs per month
Dépense mensuelle réelle pour un ratio entrée-sortie de 4:1 — le rapport effectivement observé dans une charge de travail type (chat ou RAG).
| Charge de travail | Jetons/mois | Coût par mois |
|---|---|---|
| Projet secondaire | 1 million en entrée / 0,25 million en sortie | $3.50 |
| Petite équipe | 20 millions en entrée / 5 millions en sortie | $70 |
| Production | 200 millions en entrée / 50 millions en sortie | $700 |
Calculez vos propres coûts dans le Calculateur de coûts pour les API IA.
Cheaper alternatives to Qwen3.8-Max
| Modèle | Coût combiné par million de dollars | Vous économisez |
|---|---|---|
| Llama 3.1 8B ouverte | $0.0240 | 99 % moins cher |
| Mistral NeMo 12B ouverte | $0.0292 | 99 % moins cher |
| Gemma 3 4B ouverte | $0.0600 | 98% cheaper |
Questions fréquemment posées
How much does Qwen3.8-Max cost per 1M tokens?
Qwen3.8-Max costs $2.00 per 1M input tokens and $6.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $2.80 per 1M tokens.
How much does Qwen3.8-Max cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $70 on Qwen3.8-Max. A side project (1M in / 0.25M out) costs roughly $3.50.
What is a cheaper alternative to Qwen3.8-Max?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 99% less than Qwen3.8-Max. It is also open-weight, so self-hosting is an option.
Can I run Qwen3.8-Max locally?
No. Qwen3.8-Max is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Qwen3.8-Max charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Qwen3.8-Max charges 3× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Les prix indiqués correspondent aux tarifs publics officiels pour l’API principale du modèle et sont mis à jour régulièrement à mesure que les fournisseurs les modifient. Les remises liées aux volumes, aux traitements par lots ou aux entrées mises en cache ne sont pas prises en compte. Comparez tous les modèles côte à côte dans le Base de données des modèles IA ou le Classement des grands modèles linguistiques (LLM).