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

seamless-m4t-v2-large
Memory at each precision, the licence in plain words, and where it fits.

Short answer. seamless-m4t-v2-large needs about 2.8 GB of memory at 4-bit, 4.0 GB at 8-bit and 6.1 GB at full 16-bit precision, including runtime overhead. It has about 2.3 billion parameters and a 4,096-token context window. Licence in short: non-commercial only. By memory alone, on ANVE’s launch configurations: ANVE One fits at BF16, ANVE Office fits at BF16, ANVE Office Pro (GPU) fits at BF16. These are estimates from its published size, not benchmarks.

01

What it is

seamless-m4t-v2-large is a speech-recognition model that turns recorded speech into text, published by Meta (FAIR) on Hugging Face on 29 November 2023. It has about 2.3 billion parameters and a configured context window of 4,096 tokens.

Its card lists the licence as CC BY-NC 4.0. In short, the licence allows non-commercial use only, so an office cannot use it for paid client work without a separate licence.

Hugging Face counted about 292,603 downloads of it in the 30 days before we checked (7 Oct 2026), and 1,026 people have liked it there.

The card lists 96 languages: af, am, ar, as, az, be, bn, bs, bg, ca, cs, zh and 84 more (ISO codes as given on the card).

02

How much memory it needs

The arithmetic: parameters × bits per weight ÷ 8 gives the weights, plus about 1.5 GB for the runtime. These are planning estimates, not measurements.

Speech models also need working memory for the audio being processed, which is small next to the weights.

PrecisionWeightsTotal, estimated
BF16 (full precision)4.6 GB6.1 GB
8-bit (Q8_0)2.5 GB4.0 GB
4-bit (Q4_K)1.3 GB2.8 GB
03

Architecture at a glance

SettingValue in config.json
Architecture classSeamlessM4Tv2Model
Model typeseamless_m4t_v2
Layers24
Hidden size1,024
Attention heads16
Head size64
Vocabulary256,102
Configured context4,096
Stored precisionfloat32
04

Will it fit on ANVE?

How the verdicts are worked out: on ANVE One, about three quarters of 64 GB of unified memory is available to the model; on ANVE Office and ANVE Office Pro, the model has to fit in the 24 GB on the graphics card, with 64 GB or 128 GB of system memory for everything else. This is arithmetic against the launch specification, not a test. 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 memoryfits at BF16
ANVE Office24 GB on the RTX PRO 4000 Blackwell SFF Editionfits at BF16
ANVE Office Pro (GPU)24 GB on the RTX PRO 4000 Blackwellfits at BF16
05

What an office would use it for

For an office, this is the model that turns a recorded meeting or call into a transcript. Accuracy depends heavily on the language, the microphone and how people talk over each other, so test it on your own recordings.

06

Similar models to compare

  • granite-4.0-1b-speech (2.3B parameters, about 2.8 GB at 4-bit before context; commercial use allowed)
  • Qwen3-ASR-1.7B (2.3B parameters, about 2.8 GB at 4-bit before context; commercial use allowed)
  • cohere-transcribe-03-2026 (2.1B parameters, about 2.7 GB at 4-bit before context; commercial use allowed)
07

Questions people ask

How much memory does seamless-m4t-v2-large need?
About 2.8 GB at 4-bit, 4.0 GB at 8-bit and 6.1 GB at full 16-bit precision, including about 1.5 GB of runtime overhead. These are estimates from its parameter count.
Can seamless-m4t-v2-large run on a 24 GB graphics card?
Yes, at BF16 by this estimate, with room left for context.
Is seamless-m4t-v2-large free for commercial use?
Its card lists CC BY-NC 4.0, which allows non-commercial use only, so an office cannot use it for paid client work without a separate licence. Read the licence itself before relying on this summary; it is not legal advice.
What is seamless-m4t-v2-large’s context window?
Its configuration sets 4,096 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.