How much VRAM does Qwen3-Coder-Next need?

Qwen3-Coder-Next (80B parameters) requires approximately 51.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-Coder-Next?

The recommended quantization for Qwen3-Coder-Next is Q4_K_M, which balances quality and memory efficiency.

Can it run?

No, Qwen3-Coder-Next requires more memory than RTX 3070 Ti 8GB provides.

FWon't run

Too heavy

Using Q4_K_M in Ollama

Capabilities:

Fit status

Too heavy

Decode

27.2 tok/s

TTFT

7122 ms

Safe context

Memory

51.6 GB / 8.0 GB

Weights48.8 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom0.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	F	Too heavy	27.2 tok/s	10359 ms	5K
Chat	F	Too heavy	27.2 tok/s	3885 ms	4K
Coding	F	Too heavy	27.2 tok/s	7122 ms	4K
RAG	F	Too heavy	27.2 tok/s	12949 ms	5K
Reasoning	F	Too heavy	27.2 tok/s	8417 ms	4K

How Qwen3-Coder-Next (80B params) fits at each quantization level on RTX 3070 Ti 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	31.2 GB	Low	F0
Q3_K_S	3	39.2 GB	Low	F0
NVFP4	4

Upgrade options

MacBook Pro M3 Max 128GBBudget pick

C14.9 tok/s decode

~$2,499 MSRP

MacBook Pro M4 Max 96GBBest value

C21.4 tok/s decode

~$2,499 MSRP

NVIDIA A100 80GBBiggest leap