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ANVE

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

bitnet-b1.58-2B-4T
The memory it needs, what you may do with it, and the hardware it suits.

Short answer. bitnet-b1.58-2B-4T needs about 2.6 GB of memory at 4-bit, 3.0 GB at 8-bit and 3.8 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 850 million parameters and a 4,096-token context window. Licence in short: commercial use allowed. 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

bitnet-b1.58-2B-4T is a language model for chat, drafting and question answering, published by Microsoft on Hugging Face on 15 April 2025. It has about 850 million parameters and a configured context window of 4,096 tokens.

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 20,121 downloads of it in the 30 days before we checked (7 Oct 2026), and 1,498 people have liked it there.

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 0.08 MB of KV cache at 16-bit, so 32,768 tokens would add about 2.5 GB.

PrecisionWeightsKV cache (8,192 tokens)Total, estimated
BF16 (full precision)1.7 GB0.63 GB3.8 GB
8-bit (Q8_0)0.90 GB0.63 GB3.0 GB
4-bit (Q4_K)0.48 GB0.63 GB2.6 GB
03

Architecture at a glance

SettingValue in config.json
Architecture classBitNetForCausalLM
Model typebitnet
Layers30
Hidden size2,560
Attention heads20
Key-value heads5 (grouped-query attention)
Head size128
Vocabulary128,256
Configured context4,096
Stored precisionbfloat16
04

Will it fit on ANVE?

Arithmetic against the launch specification, not a test: about three quarters of ANVE One’s 64 GB of unified memory for the model (as AMD’s Variable Graphics Memory allows), and the 24 GB on the graphics card in ANVE Office and ANVE Office Pro, which keep the rest of the stack in 64 GB and 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 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

Models this small are best for routing, classification, autocomplete and simple extraction. They are not reliable for minutes or legal drafting: ANVE never uses anything smaller than a 4B-class model for minutes.

06

Similar models to compare

  • Qwen3-0.6B (0.8B parameters, about 1.9 GB at 4-bit before context; commercial use allowed)
  • gemma-3-1b-it (1.0B parameters, about 2.1 GB at 4-bit before context; commercial use allowed, with conditions)
  • MiniCPM5-1B (1.1B parameters, about 2.1 GB at 4-bit before context; commercial use allowed)
07

Questions people ask

How much memory does bitnet-b1.58-2B-4T need?
About 2.6 GB at 4-bit, 3.0 GB at 8-bit and 3.8 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 bitnet-b1.58-2B-4T run on a 24 GB graphics card?
Yes, at BF16 by this estimate, with room left for context.
Is bitnet-b1.58-2B-4T 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 bitnet-b1.58-2B-4T’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.