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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/Mixtral 8x22B/on RTX 4070 Ti Super 16GB

Can it run?

Can RTX 4070 Ti Super 16GB run Mixtral 8x22B?

FWon't run

Too heavy

Using Q4_K_M in llama.cpp

Capabilities:

Fit status

Too heavy

Decode

12.0 tok/s

TTFT

16146 ms

Safe context

4K

Memory

94.6 GB / 16.0 GB

Memory breakdown

Weights86.0 GB
KV Cache6.1 GB
Runtime0.9 GB
Headroom1.6 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingFToo heavy12.0 tok/s23485 ms5K
ChatFToo heavy12.0 tok/s8807 ms4K
CodingFToo heavy12.0 tok/s16146 ms4K
RAGFToo heavy12.0 tok/s29356 ms5K
ReasoningFToo heavy12.0 tok/s19082 ms4K

Quantization options

How Mixtral 8x22B (141B params) fits at each quantization level on RTX 4070 Ti Super 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
55.0 GB
LowF0
Q3_K_S
3
69.1 GB
LowF0
NVFP4
4
79.0 GB
MediumF0
Q4_K_M
4
86.0 GB
MediumF0
Q5_K_M
5
101.5 GB
HighF0
Q6_K
6
115.6 GB
HighF0
Q8_0
8
150.9 GB
Very HighF0
F16
16
289.0 GB
MaximumF0

Upgrade options

Hardware that runs Mixtral 8x22B well

AppleMacBook Pro M3 Max 128GBBest value
D5.1 tok/s decode

~$2,499 MSRP

AMDAMD Instinct MI350X 288GBBudget pick
C130.3 tok/s decode

~$8,000 MSRP

NVIDIANVIDIA H200 141GBBiggest leap
B89.9 tok/s decode

~$30,000 MSRP

NVIDIANVIDIA H200 PCIe 141GBNVIDIA upgrade
B89.9 tok/s decode

~$30,000 MSRP

See all results for RTX 4070 Ti Super 16GBSee all hardware for Mixtral 8x22B