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Llama 4 Maverick 17B 128E

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35.9KDescargas489Me gustaApr 2025Publicado1.0M tokensContextoLlama 4 CommunityLicencia81 FuerteCalidad

Llama 4 Maverick 17B 128E (400B parameters) requires approximately 248.4 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 17B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 286 GB of VRAM.

Comenzar

— copia y pega para ejecutar en local

Copy-paste commands to run Llama 4 Maverick 17B 128E on your machine.

Run

lms load Llama-4-Maverick-17B-128E-Instruct && lms server start

Quick specs

Parameters400B (17B active)
Architecturemoe (MoE)
Context1.0M tokens
Modalitytext+vision
Min RAM156 GB
Rec. RAM244 GB (Q4_K_M)
LicenseLlama 4 Community
FamilyLlama
Vision Chat Reasoning

About this model

Llama 4 Maverick is Meta's large MoE model with 17B active parameters and 128 experts (400B total). Delivers frontier-class performance on reasoning and coding while remaining deployable on a single node.

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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
156.0 GB
Low
Q3_K_S
3
196.0 GB
Low
NVFP4
4
224.0 GB
Medium
Q4_K_M
4
244.0 GB
Medium
Q5_K_M
5
288.0 GB
High
Q6_K
6
328.0 GB
High
Q8_0
8
428.0 GB
Very High
F16
16
820.0 GB
Maximum

Quality benchmarks

Llama 4 Maverick 17B 128E benchmark scores

Benchmark verified

Coding

SWE-bench Verified
HumanEval+
Aider Polyglot
LiveCodeBench43.4%

Reasoning

MMLU-Pro80.5%
GPQA Diamond69.8%
MATH-50061.2%
ARC Challenge

Source: official · 2025-04-05

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

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Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

Weights244.0 GB
KV Cache2.9 GB
Runtime0.9 GB
Headroom0.6 GB

Preguntas frecuentes

FAQ — Llama 4 Maverick 17B 128E

Ver también