👁 Alibaba
Alibaba
Qwen3-Coder-Next
Frontier
1.2MDownloads1.5KLikesJan 2026Released256K tokensContextApache 2.0License93 ExceptionalQuality
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.
Get started
— copy & paste to run locallyCopy-paste commands to run Qwen3-Coder-Next on your machine.
Run
ollama run qwen3-coder-nextQuick 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
- •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...
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Your hardware
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Quick picks
Best budgetS
MacBook Pro M3 Max 128GB~$2,499 — 23 tok/s
Best overallS
NVIDIA A100 80GB~$15,000 — 116 tok/sBest hardware
Top picks for Qwen3-Coder-Next
Run this model
Quantization options
VRAM estimates by quant level
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
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
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights48.8 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Qwen3-Coder-Next
See also