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Run it on your own hardware · updated 2026-10-16

MiMo-V2.5-Pro
The memory it needs, what you may do with it, and the hardware it suits.

Short answer. MiMo-V2.5-Pro needs about 581 GB of memory at 4-bit, 1,092 GB at 8-bit and 2,051 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 1,023.2 billion parameters and a 1,048,576-token context window. Licence in short: commercial use allowed. By memory alone, on ANVE’s launch configurations: ANVE One does not fit, ANVE Office does not fit, ANVE Office Pro (GPU) does not fit. These are estimates from its published size, not benchmarks.

01

What it is

MiMo-V2.5-Pro is a language model for chat, drafting and question answering, published by Xiaomi on Hugging Face on 27 April 2026. It has about 1,023.2 billion parameters and a configured context window of 1,048,576 tokens. It is a mixture-of-experts model: 384 experts, 8 used for each token.

Its card lists the licence as MIT. In short, the licence allows commercial use, modification and redistribution as long as the copyright notice is kept.

Hugging Face counted about 22,052 downloads of it in the 30 days before we checked (7 Oct 2026), and 762 people have liked it there.

The card lists 2 languages: en, zh (ISO codes as given on the card).

02

How much memory it needs

The arithmetic: parameters × bits per weight ÷ 8 gives the weights; add the KV cache, which grows with every token of context; then add about 1.5 GB for the runtime. These are estimates for planning, not measurements.

Each token of context adds about 0.43 MB of KV cache at 16-bit, so 32,768 tokens would add about 14 GB.

PrecisionWeightsKV cache (8,192 tokens)Total, estimated
BF16 (full precision)2,046 GB3.5 GB2,051 GB
8-bit (Q8_0)1,087 GB3.5 GB1,092 GB
4-bit (Q4_K)576 GB3.5 GB581 GB
03

Architecture at a glance

SettingValue in config.json
Architecture classMiMoV2ForCausalLM
Model typemimo_v2
Layers70
Hidden size6,144
Attention heads128
Key-value heads8 (grouped-query attention)
Head size192
Vocabulary152,576
Experts384, 8 active per token
Configured context1,048,576
Stored precisionbfloat16
04

Will it fit on ANVE?

These verdicts are arithmetic, not tests, against the specification at launch: ANVE One can give a model about three quarters of its 64 GB of unified memory, while ANVE Office and ANVE Office Pro hold it on a 24 GB graphics card and keep the rest of the stack in 64 GB or 128 GB of system memory. ANVE’s tested default is Qwen 3.8 27B; this model is not yet validated on ANVE.

Configuration (at launch)Memory for the modelVerdict
ANVE Oneabout 48 GB of 64 GB unified memorydoes not fit
ANVE Office24 GB on the RTX PRO 4000 Blackwell SFF Editiondoes not fit
ANVE Office Pro (GPU)24 GB on the RTX PRO 4000 Blackwelldoes not fit
05

What an office would use it for

This is frontier-scale: even at 4-bit it needs far more memory than any single office box, so it belongs on a multi-GPU server or a cloud service, not on an appliance.

06

Similar models to compare

  • Kimi-K2-Instruct (1026.4B parameters, about 579 GB at 4-bit before context; custom licence: check before commercial use)
  • GLM-5.3 (753.3B parameters, about 425 GB at 4-bit before context; custom licence: check before commercial use)
  • GLM-5.2 (753.3B parameters, about 425 GB at 4-bit before context; commercial use allowed)
07

Questions people ask

How much memory does MiMo-V2.5-Pro need?
About 581 GB at 4-bit, 1,092 GB at 8-bit and 2,051 GB at full 16-bit precision, including an 8,192-token KV cache and about 1.5 GB of runtime overhead. These are estimates from its parameter count.
Can MiMo-V2.5-Pro run on a 24 GB graphics card?
Not entirely: even at 4-bit it needs about 581 GB, so part of it would sit in system memory, which is much slower.
Is MiMo-V2.5-Pro free for commercial use?
Its card lists MIT, which allows commercial use, modification and redistribution as long as the copyright notice is kept. Read the licence itself before relying on this summary; it is not legal advice.
What is MiMo-V2.5-Pro’s context window?
Its configuration sets 1,048,576 tokens. Longer contexts need more memory for the KV cache, so the practical limit on a given machine can be lower.
08

What is not real yet

No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.

Reservations are ₹999 in India or US$12 elsewhere, refundable in full until you confirm an order in writing (terms). Offices that cannot use cloud AI can apply to be one of ten design partners.