v2.2 · 2026-06-12

OLMo 2 1124 13B Instruct

olmo-2-1124-13b-instruct

TEXT-CHAT

OLMo 2 1124 13B Instruct is a 14B text chat model profile for local AI planning. This page records provider, license, context, quantization, hardware-fit estimates, setup hints, source links, and caveats so readers do not choose a model by name alone.

PROVIDER

Ai2 / Allen Institute for AI

FAMILY

OLMo 2

MODEL TYPE

text-chat

PARAMETERS

14B

MODALITIES

text

ARCHITECTURE

OLMo 2 decoder-only transformer, post-trained with Tülu 3 supervised fine-tuning, DPO and reinforcement learning with verifiable rewards.

CONTEXT WINDOW

4,096 tokens

TRAINING TOKENS

—

RELEASE DATE

2024-11-26

LICENSE & LINKS

Apache-2.0license text

MODEL CARD

huggingface.co/allenai/OLMo-2-1124-13B-Instruct

HUGGING FACE

allenai/OLMo-2-1124-13B-Instruct

GGUF REPOSITORIES

allenai/OLMo-2-1124-13B-Instruct-GGUF official

Official Ai2 GGUF repository with Q4_K_M, Q5_K_M and Q8_0 file listings; GGUF metadata reports model size as 14B although the checkpoint is named 13B.

SETUP HINTS

OLLAMA

Run `ollama run olmo2:13b` or a specific quantized tag such as `olmo2:13b-q4_K_M`.

LM STUDIO

Use the official `allenai/OLMo-2-1124-13B-Instruct-GGUF` repository and select Q4_K_M for most local systems.

LLAMA.CPP

Use a standard text GGUF loader against the official Ai2 GGUF repository.

QUANTIZATION FILE SIZES (GGUF)

Q4_K_M

8.35 GB

Q5_K_M

9.76 GB

Q8_0

14.6 GB

Quantization note: Q4_K_M for 16GB+ systems; Q5_K_M or Q8_0 only on 32GB RAM, ample unified memory or larger VRAM systems.

RAM / VRAM ESTIMATES

MIN RAM

16 GB

COMFORTABLE RAM

32 GB

MIN VRAM

10 GB

COMFORTABLE VRAM

16 GB

These are conservative local-inference estimates, not official hardware requirements.

HARDWARE FIT

CPU only (no GPU)

limited

8 GB RAM

16 GB RAM

limited

32 GB RAM

yes

8 GB VRAM

12 GB VRAM

limited

24 GB VRAM

yes

Apple Silicon (unified memory)

yes

Hardware fit values are conservative local-inference estimates based on GGUF size plus runtime and KV-cache overhead. Actual requirements depend on context length, quantization, runtime, GPU offload, and other running apps.

BEST FOR

·Stronger fully open OLMo 2 local chat than the 7B variant

·Research and education

·General chat and summarization on 32GB-class systems

·Open-science model comparison

AVOID IF

·You only have 8GB RAM or 8GB VRAM

·You need verified structured tool calling

·You need multilingual support beyond primarily English

·You need vision

CAVEATS

·The model is named 13B, but the official GGUF metadata reports model size as 14B; `parameterSizeB` follows the GGUF metadata.

·Ollama and release sources describe the OLMo 2 family as trained up to 5T tokens, but the exact instruct checkpoint token count was not separately verified, so `trainingTokens` is null.

·The official model card describes the language as primarily English.

·The model card does not verify structured tool-calling support, so `supportsTools` is null.

·RAM and VRAM estimates are derived from GGUF/Ollama package size plus conservative overhead; KV cache, context length, batch size, runtime and GPU offload choices can materially change memory needs.

SOURCE URLS