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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Qwen3-Coder-Next/on GTX 1660 Super 6GB

Can it run?

Can GTX 1660 Super 6GB run Qwen3-Coder-Next?

FWon't run

Too heavy

Using Q4_K_M in Ollama

Capabilities:

Fit status

Too heavy

Decode

11.5 tok/s

TTFT

16871 ms

Safe context

4K

Memory

51.4 GB / 6.0 GB

Memory breakdown

Weights48.8 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom0.6 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingFToo heavy11.5 tok/s24539 ms4K
ChatFToo heavy11.5 tok/s9202 ms4K
CodingFToo heavy11.5 tok/s16871 ms4K
RAGFToo heavy11.5 tok/s30674 ms4K
ReasoningFToo heavy11.5 tok/s19938 ms4K

Quantization options

How Qwen3-Coder-Next (80B params) fits at each quantization level on GTX 1660 Super 6GB (6.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
31.2 GB
LowF0
Q3_K_S
3
39.2 GB
LowF0
NVFP4
4
44.8 GB
MediumF0
Q4_K_M
4
48.8 GB
MediumF0
Q5_K_M
5
57.6 GB
HighF0
Q6_K
6
65.6 GB
HighF0
Q8_0
8
85.6 GB
Very HighF0
F16
16
164.0 GB
MaximumF0

Upgrade options

Hardware that runs Qwen3-Coder-Next well

AppleMacBook Pro M3 Max 128GBBudget pick
C14.9 tok/s decode

~$2,499 MSRP

AppleMacBook Pro M4 Max 96GBBest value
C21.4 tok/s decode

~$2,499 MSRP

NVIDIANVIDIA A100 80GBBiggest leap
B106.4 tok/s decode

~$15,000 MSRP

NVIDIANVIDIA A800 80GBNVIDIA upgrade
B93.7 tok/s decode

 

See all results for GTX 1660 Super 6GBSee all hardware for Qwen3-Coder-Next