Alibaba

Qwen3-Coder-Next

Name: Qwen3-Coder-Next
Rating: 89 (44 reviews)
Author: Alibaba

Frontera

HuggingFace

Ollama

937.9KDescargas1.4KMe gustaJan 2026Publicado256K tokensContextoApache 2.0Licencia93 ExcepcionalCalidad

Qwen3-Coder-Next (80B parameters) requires approximately 52.1 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 3B 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 60 GB of VRAM.

Comenzar

— copia y pega para ejecutar en local

Copy-paste commands to run Qwen3-Coder-Next on your machine.

Run

ollama run qwen3-coder-next

Quick specs

Parameters80B (3B active)

Architecturemoe (MoE)

Context256K tokens

Modalitytext

Min RAM31.2 GB

Rec. RAM48.8 GB (Q4_K_M)

LicenseApache 2.0

FamilyQwen Coder

✓ Code✓ Reasoning

About this model

Today, we're announcing Qwen3-Coder-Next, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements:

•Super Efficient with Significant Performance: With only 3B activated parameters (80B total parameters), it achieves performance comparable to...
•Advanced Agentic Capabilities: Through an elaborate training recipe, it excels at long-horizon reasoning, complex tool usage, and recovery from...
•Versatile Integration with Real-World IDE: Its 256k context length, combined with adaptability to various scaffold templates, enables seamless...

Modelos relacionados

Selecciones rápidas

Mejor económicoS

MacBook Pro M3 Max 128GB~$2,499 — 23 tok/s

Mejor en generalS

NVIDIA A100 80GB~$15,000 — 116 tok/s

Mejor hardware

Mejores opciones para Qwen3-Coder-Next

NVIDIA H100 PCIe 80GBS

80 GB

Ejecutar este modelo

Qwen3-Coder-Next on NVIDIA A100 80GB Qwen3-Coder-Next on NVIDIA H100 80GB Qwen3-Coder-Next on NVIDIA A800 80GB

Opciones de cuantización

Estimaciones de VRAM por nivel de cuantización

No hardware detected — fit column shows raw VRAM estimates

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	31.2 GB	Low	—
Q3_K_S	3	39.2 GB	Low	—
NVFP4	4	44.8 GB	Medium	—
Q4_K_M	4	48.8 GB	Medium	—
Q5_K_M	5	57.6 GB	High	—
Q6_K	6	65.6 GB	High	—
Q8_0	8	85.6 GB	Very High	—
F16	16	164.0 GB	Maximum	—

Quality benchmarks

Qwen3-Coder-Next benchmark scores

Benchmark verified

Coding

SWE-bench Verified70.6%

HumanEval+—

Aider Polyglot—

LiveCodeBench74.5%

Reasoning

MMLU-Pro78.4%

GPQA Diamond—

MATH-500—

ARC Challenge—

Source: official · 2026-01-30

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

Abrir calculadora

Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

Weights48.8 GB

KV Cache1.5 GB

Runtime1.2 GB

Headroom0.6 GB

Preguntas frecuentes

FAQ — Qwen3-Coder-Next

Ver también

Guía de cuantización Metodología de puntuación Abrir calculadora