internlm2-chat-20b The memory it needs, what you may do with it, and the hardware it suits.
Short answer. internlm2-chat-20b needs about 14 GB of memory at 4-bit, 24 GB at 8-bit and 43 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 19.9 billion parameters and a 32,768-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 4-bit, ANVE Office Pro (GPU) fits at 4-bit. These are estimates from its published size, not benchmarks.
01
What it is
internlm2-chat-20b is a language model for chat, drafting and question answering, published by Shanghai AI Laboratory on Hugging Face on 10 January 2024. It has about 19.9 billion parameters and a configured context window of 32,768 tokens.
Its card lists the licence as a custom licence (other). In short, the licence sets its own terms; read it before any commercial use.
Hugging Face counted about 21,192 downloads of it in the 30 days before we checked (7 Oct 2026), and 88 people have liked it there.
02
How much memory it needs
How these figures are worked out: weights = parameters × bits per weight ÷ 8. The KV cache is added for 8,192 tokens of context, plus about 1.5 GB of runtime overhead. Treat the totals as planning estimates.
Each token of context adds about 0.20 MB of KV cache at 16-bit, so 32,768 tokens would add about 6.4 GB.
Precision
Weights
KV cache (8,192 tokens)
Total, estimated
BF16 (full precision)
40 GB
1.6 GB
43 GB
8-bit (Q8_0)
21 GB
1.6 GB
24 GB
4-bit (Q4_K)
11 GB
1.6 GB
14 GB
03
Architecture at a glance
Setting
Value in config.json
Architecture class
InternLM2ForCausalLM
Model type
internlm2
Layers
48
Hidden size
6,144
Attention heads
48
Key-value heads
8 (grouped-query attention)
Head size
128
Vocabulary
92,544
Configured context
32,768
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 BF16
ANVE Office
24 GB on the RTX PRO 4000 Blackwell SFF Edition
fits at 4-bit
ANVE Office Pro (GPU)
24 GB on the RTX PRO 4000 Blackwell
fits at 4-bit
05
What an office would use it for
This is the class ANVE runs by default (27B-class): strong enough for meeting minutes, summaries, drafting and question answering over an office’s own documents, and small enough for one box.
06
Similar models to compare
gpt-oss-20b (20.9B parameters, about 13 GB at 4-bit before context; commercial use allowed)
ERNIE-4.5-21B-A3B-Thinking (21.8B parameters, about 14 GB at 4-bit before context; commercial use allowed)
EuroLLM-22B-Instruct-2512 (22.6B parameters, about 14 GB at 4-bit before context; commercial use allowed)
07
Questions people ask
How much memory does internlm2-chat-20b need?
About 14 GB at 4-bit, 24 GB at 8-bit and 43 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 internlm2-chat-20b run on a 24 GB graphics card?
Yes, at 4-bit by this estimate, with room left for context.
Is internlm2-chat-20b free for commercial use?
Its card lists a custom licence (other), 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 internlm2-chat-20b’s context window?
Its configuration sets 32,768 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.
