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OLMo 2 13B

Actual
Nov 2024Publicado33K tokensContextoApache 2.0Licencia64 BuenoCalidad

OLMo 2 13B (13B parameters) requires approximately 11.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 14 GB of VRAM.

Comenzar

— copia y pega para ejecutar en local

Copy-paste commands to run OLMo 2 13B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "allenai/OLMo-2-13B-Instruct" \ --hf-file "OLMo-2-13B-Instruct-Q4_K_M.gguf" \ -c 4096 -ngl 99

Quick specs

Parameters13B
Architecturedense
Context33K tokens
Modalitytext
Min RAM5.1 GB
Rec. RAM7.9 GB (Q4_K_M)
LicenseApache 2.0
FamilyOLMo
Chat

About this model

OLMo 2 13B is AI2's fully open research model with transparent training data and methodology. Designed for reproducible research with competitive performance on reasoning and general knowledge tasks.

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Opciones de cuantización

Estimaciones de VRAM por nivel de cuantización

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
Low
Q3_K_S
3
6.4 GB
Low
NVFP4
4
7.3 GB
Medium
Q4_K_M
4
7.9 GB
Medium
Q5_K_M
5
9.4 GB
High
Q6_K
6
10.7 GB
High
Q8_0
8
13.9 GB
Very High
F16
16
26.7 GB
Maximum

Quality benchmarks

OLMo 2 13B benchmark scores

Benchmark verified

General

Chatbot Arena
IFEval82.6%

Source: official · 2024-11-24

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

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Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

Weights7.9 GB
KV Cache2.4 GB
Runtime0.9 GB
Headroom0.6 GB

Preguntas frecuentes

FAQ — OLMo 2 13B

Ver también