How much memory does OLMo-2-1124-13B-Instruct need?

About 16 GB at 4-bit, 23 GB at 8-bit and 36 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 OLMo-2-1124-13B-Instruct run on a 24 GB graphics card?

Yes, at 8-bit by this estimate, with room left for context.

What is OLMo-2-1124-13B-Instruct’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.

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ANVE

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

OLMo-2-1124-13B-Instruct
How much memory it needs, what its licence allows, and whether it fits an office box.

Short answer. OLMo-2-1124-13B-Instruct needs about 16 GB of memory at 4-bit, 23 GB at 8-bit and 36 GB at full 16-bit precision, including runtime overhead and an 8,192-token KV cache. It has about 13.7 billion 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 8-bit, ANVE Office Pro (GPU) fits at 8-bit. These are estimates from its published size, not benchmarks.

What it is

OLMo-2-1124-13B-Instruct is a language model for chat, drafting and question answering, published by the Allen Institute for AI (Ai2) on Hugging Face on 18 December 2024. It has about 13.7 billion parameters and a configured context window of 4,096 tokens.

Its card lists the licence as Apache 2.0. In short, the licence allows commercial use, modification and redistribution, with attribution and a copy of the licence, and includes a patent grant.

Hugging Face counted about 13,792 downloads of it in the 30 days before we checked (7 Oct 2026), and 48 people have liked it there.

It is built on allenai/OLMo-2-1124-13B-Instruct-RLVR2, according to its card.

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 0.82 MB of KV cache at 16-bit, so 32,768 tokens would add about 27 GB.

Precision	Weights	KV cache (8,192 tokens)	Total, estimated
BF16 (full precision)	27 GB	6.7 GB	36 GB
8-bit (Q8_0)	15 GB	6.7 GB	23 GB
4-bit (Q4_K)	7.7 GB	6.7 GB	16 GB

Architecture at a glance

Setting	Value in config.json
Architecture class	Olmo2ForCausalLM
Model type	olmo2
Layers	40
Hidden size	5,120
Attention heads	40
Key-value heads	40
Head size	128
Vocabulary	100,352
Configured context	4,096
Stored precision	bfloat16

Will it fit on ANVE?

These verdicts are arithmetic, not tests, against the specification at launch: ANVE One can give a model about three quarters of its 64 GB of unified memory, while ANVE Office and ANVE Office Pro hold it on a 24 GB graphics card and keep the rest of the stack in 64 GB or 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 8-bit
ANVE Office Pro (GPU)	24 GB on the RTX PRO 4000 Blackwell	fits at 8-bit

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.

Similar models to compare

Phi-3-medium-4k-instruct (14.0B parameters, about 9.4 GB at 4-bit before context; commercial use allowed)
phi-4 (14.7B parameters, about 9.7 GB at 4-bit before context; commercial use allowed)
Phi-4-reasoning (14.7B parameters, about 9.7 GB at 4-bit before context; commercial use allowed)

Questions people ask

How much memory does OLMo-2-1124-13B-Instruct need?: About 16 GB at 4-bit, 23 GB at 8-bit and 36 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 OLMo-2-1124-13B-Instruct run on a 24 GB graphics card?: Yes, at 8-bit by this estimate, with room left for context.
Is OLMo-2-1124-13B-Instruct free for commercial use?: Its card lists Apache 2.0, which allows commercial use, modification and redistribution, with attribution and a copy of the licence, and includes a patent grant. Read the licence itself before relying on this summary; it is not legal advice.
What is OLMo-2-1124-13B-Instruct’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.

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.

OLMo-2-1124-13B-InstructHow much memory it needs, what its licence allows, and whether it fits an office box.