Qwen3-Max
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Alibaba
- Organisation type
- Industry
- Country
- China
- Published
- 5 September 2025
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Question answering, Mathematical reasoning, Code generation, Quantitative reasoning, Retrieval-augmented generation, Translation
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 1T
- Training data
- 36,000,000,000,000 tokens
MoE architecture
"was pretrained on 36 trillion tokens"
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 1.5 × 10²⁵ FLOP
- How it was established
- Operation counting
6ND with: 36T tokens is taken from the qwen3 technical report 70B active params is based on it having >1T params, and the architectures of Qwen3-235B-A22B and Qwen3-Coder-480B-A35B
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- API access
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Likely above 10²³ FLOP
- Yes
- Why it is tracked
- Discretionary
- Record confidence
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing Qwen3-Max-Preview (Instruct) — our biggest model yet, with over 1 trillion parameters!
- Last updated
- 18 December 2025
What the numbers mean
What this model is
Qwen3-Max was published by Alibaba, in the country recorded as China, during September 2025. The category the publisher falls under is industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation, Question answering, Mathematical reasoning, Code generation, Quantitative reasoning, Retrieval-augmented generation, Translation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
Training it took a computation budget of roughly 1.5 × 10²⁵ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Training consumed a corpus of around 36,000,000,000,000 tokens of text.
It is tracked in the underlying dataset for one reason in particular: discretionary.
Answers
Qwen3-Max — common questions
Qwen3-Max— who created it?
It was published by Alibaba, based in China, an organisation categorised as industry.
Qwen3-Max— when was it released?
It was published in September 2025.
Qwen3-Max— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Question answering, Mathematical reasoning, Code generation, Quantitative reasoning, Retrieval-augmented generation, Translation. These are the areas it was designed around; they describe intent rather than a hard boundary.
Qwen3-Max— how much compute was used to train it?
Training consumed around 1.5 × 10²⁵ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
Qwen3-Max— what GPU do I need to run it?
None. This is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Qwen3-Max— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Qwen3-Max— how many parameters does it have?
It has a parameter count of 1T. MoE architecture. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.