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Phi-4-reasoning-plus 14B

Frontera
huggingfaceHuggingFaceollamaOllama
19.7KDescargas340Me gustaApr 2025Publicado33K tokensContextoMITLicencia92 ExcepcionalCalidad

Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 13.8 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 16 GB of VRAM.

Comenzar

— copia y pega para ejecutar en local

Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.

Run

ollama run phi4-reasoning

Quick specs

Parameters14.7B
Architecturedense
Context33K tokens
Modalitytext
Min RAM5.7 GB
Rec. RAM9 GB (Q4_K_M)
LicenseMIT
FamilyPhi
✓ Chat✓ Reasoning

About this model

> [!IMPORTANT] > To fully take advantage of the model's capabilities, inference must use `temperature=0.8`, `top_k=50`, `top_p=0.95`, and `do_sample=True`. For more complex queries, set `max_new_tokens=32768` to allow for longer chain-of-thought (CoT).

  • •AIME 2025, 2024, 2023, and 2022:: Math olympiad questions
  • •GPQA-Diamond:: Complex, graduate-level science questions
  • •OmniMath:: Collection of over 4000 olympiad-level math problems with human annotation
  • •LiveCodeBench:: Code generation benchmark gathered from competitive coding contests
  • •3SAT (3-literal Satisfiability Problem) and TSP (Traveling Salesman Problem):: Algorithmic problem solving

Modelos relacionados

Tu hardware

Detectando...

Selecciones rápidas

Mejor económicoS
RX 7600 XT 16GB~$329 — 20 tok/s
NVIDIA
Mejor en generalS
RTX 4090 24GB~$1,599 — 92 tok/s

Mejor hardware

Mejores opciones para Phi-4-reasoning-plus 14B

NVIDIA
RTX 4090 24GBS
24 GB
NVIDIA
RTX 5090 Laptop 24GBS
24 GB
NVIDIA
NVIDIA A30 24GBS
24 GB
NVIDIA
RTX 3090 Ti 24GBS
24 GB
NVIDIA
RTX A4500 20GBS
20 GB

Ejecutar este modelo

Phi-4-reasoning-plus 14B on RTX 4090 24GBPhi-4-reasoning-plus 14B on RTX 5090 Laptop 24GBPhi-4-reasoning-plus 14B on NVIDIA A30 24GB

Opciones de cuantización

Estimaciones de VRAM por nivel de cuantización

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
5.7 GB
Low—
Q3_K_S
3
7.2 GB
Low—
NVFP4
4
8.2 GB
Medium—
Q4_K_M
4
9.0 GB
Medium—
Q5_K_M
5
10.6 GB
High—
Q6_K
6
12.1 GB
High—
Q8_0
8
15.7 GB
Very High—
F16
16
30.1 GB
Maximum—

Quality benchmarks

Phi-4-reasoning-plus 14B benchmark scores

Benchmark verified

Coding

SWE-bench Verified—
HumanEval+92.3%
Aider Polyglot—
LiveCodeBench53.1%

Reasoning

MMLU-Pro76.0%
GPQA Diamond68.9%
MATH-50095.4%
ARC Challenge—

General

Chatbot Arena—
IFEval84.9%

Source: official · 2025-04-30

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

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Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

Weights9.0 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom0.6 GB

Preguntas frecuentes

FAQ — Phi-4-reasoning-plus 14B

Ver también

Guía de cuantizaciónMetodología de puntuaciónAbrir calculadora