Phi-3.5-MoE-instruct The memory it needs, what you may do with it, and the hardware it suits.
Short answer. Phi-3.5-MoE-instruct needs about 26 GB of memory at 4-bit, 47 GB at 8-bit and 86 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 41.9 billion parameters and a 131,072-token context window. Licence in short: commercial use allowed. By memory alone, on ANVE’s launch configurations: ANVE One fits at 8-bit, ANVE Office only with partial offload to system memory, which is much slower, ANVE Office Pro (GPU) only with partial offload to system memory, which is much slower. These are estimates from its published size, not benchmarks.
01
What it is
Phi-3.5-MoE-instruct is a language model for chat, drafting and question answering, published by Microsoft on Hugging Face on 17 August 2024. It has about 41.9 billion parameters and a configured context window of 131,072 tokens. It is a mixture-of-experts model: 16 experts, 2 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 141,765 downloads of it in the 30 days before we checked (7 Oct 2026), and 579 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 0.13 MB of KV cache at 16-bit, so 32,768 tokens would add about 4.3 GB.
Precision
Weights
KV cache (8,192 tokens)
Total, estimated
BF16 (full precision)
84 GB
1.1 GB
86 GB
8-bit (Q8_0)
44 GB
1.1 GB
47 GB
4-bit (Q4_K)
24 GB
1.1 GB
26 GB
03
Architecture at a glance
Setting
Value in config.json
Architecture class
PhiMoEForCausalLM
Model type
phimoe
Layers
32
Hidden size
4,096
Attention heads
32
Key-value heads
8 (grouped-query attention)
Head size
128
Vocabulary
32,064
Experts
16, 2 active per token
Configured context
131,072
Stored precision
bfloat16
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 model
Verdict
ANVE One
about 48 GB of 64 GB unified memory
fits at 8-bit
ANVE Office
24 GB on the RTX PRO 4000 Blackwell SFF Edition
only with partial offload to system memory, which is much slower
ANVE Office Pro (GPU)
24 GB on the RTX PRO 4000 Blackwell
only with partial offload to system memory, which is much slower
05
What an office would use it for
Models this large are stronger on long, hard drafting and reasoning, but need most of a 64 to 128 GB machine even at 4-bit, which leaves less room for long documents and several users.
06
Similar models to compare
Seed-OSS-36B-Instruct (36.2B parameters, about 22 GB at 4-bit before context; commercial use allowed)
Kimi-Linear-48B-A3B-Instruct (49.1B parameters, about 29 GB at 4-bit before context; commercial use allowed)
Llama-3_3-Nemotron-Super-49B-v1_5 (49.9B parameters, about 30 GB at 4-bit before context; custom licence: check before commercial use)
07
Questions people ask
How much memory does Phi-3.5-MoE-instruct need?
About 26 GB at 4-bit, 47 GB at 8-bit and 86 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 Phi-3.5-MoE-instruct run on a 24 GB graphics card?
Not entirely: even at 4-bit it needs about 26 GB, so part of it would sit in system memory, which is much slower.
Is Phi-3.5-MoE-instruct 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 Phi-3.5-MoE-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.
