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Qwen3-Coder-Next (80B-A3B)

Qwen3-Coder-Next (80B-A3B) by Alibaba Qwen (80B parameters, MoE with 3B active per token). At Q4_K_M with an 8K context it needs about 48.1 GiB of memory. An 80B coding MoE with only 3B active, and just 12 of its 48 layers keep a KV cache, so long contexts stay cheap. At 4-bit a 64 GB machine is borderline; 96 GB is comfortable.

Last updated: 2026-10-13

Model facts

DeveloperAlibaba Qwen
Parameters80B (3B active, MoE)[src]
Native context262,144 tokens[src]
LicenceApache-2.0[src]
Commercial useYes
KV cache12 of 48 layers (the rest are linear attention with a fixed-size state)[src]
Released2026-02

Good for: coding · agentic coding · long context · 64GB+ unified-memory machines

Run it

ollama run qwen3-coder-next:q4_K_M

Memory needed

Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.

Quantization4K context8K context32K context
Q4_K_M48.0 GiB48.1 GiB48.7 GiB
Q5_K_M56.2 GiB56.3 GiB56.9 GiB
Q6_K65.0 GiB65.1 GiB65.7 GiB
Q8_083.7 GiB83.8 GiB84.4 GiB
FP16157.1 GiB157.1 GiB157.7 GiB

Which hardware runs it

Best quantization that fits each device with a 8K context. Estimates, not benchmarks. See the methodology.

HardwareMemoryBest quanttok/s (est.)
RTX PRO 6000 Blackwell Workstation Edition96 GBQ8_0394
RTX PRO 5000 72GB Blackwell72 GBQ6_K381
M5 Ultra512 GBFP16130
M5 Max (18-core CPU / 40-core GPU)128 GBQ8_0125
M4 Max (16-core CPU / 40-core GPU)128 GBQ8_0111
M3 Ultra512 GBFP1689
RTX Spark (N1X) laptops & compact desktops128 GBQ8_056
DGX Spark128 GBQ8_051
Ryzen AI Max+ PRO 495 (Gorgon Halo) systems192 GBQ8_051
Ryzen AI Max+ 395 (Strix Halo) systems128 GBQ8_048
GeForce RTX 3060 (12 GB)12 GBDoesn't fit–
GeForce RTX 309024 GBDoesn't fit–
GeForce RTX 4060 Ti 16GB16 GBDoesn't fit–
GeForce RTX 4080 SUPER16 GBDoesn't fit–
GeForce RTX 409024 GBDoesn't fit–
GeForce RTX 5060 Ti 16GB16 GBDoesn't fit–
GeForce RTX 507012 GBDoesn't fit–
GeForce RTX 5070 Ti16 GBDoesn't fit–
GeForce RTX 508016 GBDoesn't fit–
GeForce RTX 509032 GBDoesn't fit–
Radeon RX 7900 XT20 GBDoesn't fit–
Radeon RX 7900 XTX24 GBDoesn't fit–
Radeon RX 9060 XT 16GB16 GBDoesn't fit–
Radeon RX 9070 XT16 GBDoesn't fit–
Arc B58012 GBDoesn't fit–
RTX A600048 GBDoesn't fit–
RTX 6000 Ada Generation48 GBDoesn't fit–
Radeon AI PRO R970032 GBDoesn't fit–
Arc Pro B6024 GBDoesn't fit–
Arc Pro B7032 GBDoesn't fit–
M4 Pro64 GBDoesn't fit–
M4 Max (14-core CPU / 32-core GPU)36 GBDoesn't fit–
M532 GBDoesn't fit–
M5 Pro64 GBDoesn't fit–
M5 Max (18-core CPU / 32-core GPU)36 GBDoesn't fit–
M6 (16GB configuration, 153 GB/s)16 GBDoesn't fit–
M6 (24GB/32GB configurations, 170 GB/s)32 GBDoesn't fit–

Frequently asked questions

How much VRAM does Qwen3-Coder-Next (80B-A3B) need?

With an 8K context, about 48.1 GiB at Q4_K_M and 83.8 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.

Can Qwen3-Coder-Next (80B-A3B) run on an GeForce RTX 4090?

Qwen3-Coder-Next (80B-A3B) does not fit on the GeForce RTX 4090 (24 GB), even at Q4_K_M with an 8K context.

Can I run Qwen3-Coder-Next (80B-A3B) on a Mac?

Yes. Qwen3-Coder-Next (80B-A3B) fits on the M3 Ultra (96 GB) at Q6_K with an 8K context, using about 65.1 GiB, at an estimated 215 tokens/s.

Can Qwen3-Coder-Next (80B-A3B) be used commercially?

Qwen3-Coder-Next (80B-A3B) is released under Apache-2.0. The licence allows commercial use (read its conditions).

Sources