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

Falcon-H1-3B-Instruct
The memory it needs, what you may do with it, and the hardware it suits.

Short answer. Falcon-H1-3B-Instruct needs about 3.5 GB of memory at 4-bit, 5.1 GB at 8-bit and 8.1 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 3.1 billion parameters and a 131,072-token context window. Licence in short: custom licence: check before commercial use. 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

Falcon-H1-3B-Instruct is a language model for chat, drafting and question answering, published by TII on Hugging Face on 1 May 2025. It has about 3.1 billion parameters and a configured context window of 131,072 tokens.

Its card lists the licence as a custom licence (falcon-llm-license). In short, the licence sets its own terms; read it before any commercial use.

Hugging Face counted about 25,162 downloads of it in the 30 days before we checked (7 Oct 2026), and 15 people have liked it there.

The card lists 18 languages: ar, cs, de, en, es, fr, hi, it, ja, ko, nl, pl and 6 more (ISO codes as given on the card).

It is built on tiiuae/Falcon-H1-3B-Base, according to its 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 0.03 MB of KV cache at 16-bit, so 32,768 tokens would add about 1.1 GB.

PrecisionWeightsKV cache (8,192 tokens)Total, estimated
BF16 (full precision)6.3 GB0.27 GB8.1 GB
8-bit (Q8_0)3.3 GB0.27 GB5.1 GB
4-bit (Q4_K)1.8 GB0.27 GB3.5 GB
03

Architecture at a glance

SettingValue in config.json
Architecture classFalconH1ForCausalLM
Model typefalcon_h1
Layers32
Hidden size2,560
Attention heads10
Key-value heads2 (grouped-query attention)
Head size128
Vocabulary65,537
Configured context131,072
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

This size suits quick drafting, classification, extraction and chat over short documents on modest hardware. ANVE pairs a fast 4B-class model with its main model for quick jobs.

06

Similar models to compare

  • Llama-3.2-3B-Instruct (3.2B parameters, about 3.3 GB at 4-bit before context; commercial use allowed, with conditions)
  • Qwen2.5-3B-Instruct (3.1B parameters, about 3.2 GB at 4-bit before context; research and non-commercial only)
  • SmolLM3-3B (3.1B parameters, about 3.2 GB at 4-bit before context; commercial use allowed)
07

Questions people ask

How much memory does Falcon-H1-3B-Instruct need?
About 3.5 GB at 4-bit, 5.1 GB at 8-bit and 8.1 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 Falcon-H1-3B-Instruct run on a 24 GB graphics card?
Yes, at BF16 by this estimate, with room left for context.
Is Falcon-H1-3B-Instruct free for commercial use?
Its card lists a custom licence (falcon-llm-license), which sets its own terms; read it before any commercial use. Read the licence itself before relying on this summary; it is not legal advice.
What is Falcon-H1-3B-Instruct’s context window?
Its configuration sets 131,072 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.