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Can Intel Arc A770 16GB run Mistralai Mixtral 8x22b Instruct V0 1?

Mistralai Mixtral 8x22b Instruct V0 1 speed on Intel Arc A770 16GB and quantization-level VRAM fit.

Q4 not recommended16GB VRAM availableRequires 71GB+

Intel Arc A770 16GB does not meet the minimum VRAM requirement for Q4 inference of Mistralai Mixtral 8x22b Instruct V0 1. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

Buy options for Intel Arc A770 16GBBest GPU guidesCompare prebuilt systems
Short answer: Intel Arc A770 16GB is not a comfortable Q4 fit for Mistralai Mixtral 8x22b Instruct V0 1 (about 71GB needed).
Estimated speed
22 tok/s
VRAM needed
71GB
VRAM headroom
-55GB

What this means for you

Intel Arc A770 16GB lacks sufficient VRAM for comfortable Mistralai Mixtral 8x22b Instruct V0 1 operation with Q4 quantization.

Your 16GB GPU is 55GB short of the 71GB minimum.

Options: (1) Try Q2 or Q3 quantization for lower VRAM requirements, (2) Consider cloud GPU rental, (3) Upgrade to a GPU with at least 16GB VRAM.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q471GB16GB22.43 tok/s❌ Not recommended
Q8141GB16GB15.70 tok/s❌ Not recommended
FP16282GB16GB8.52 tok/s❌ Not recommended

Suitable alternatives

AMD Instinct MI300X
192GB
198.45 tok/s
Price: —
Fit note: higher estimated speed than the baseline option.
Check Mistralai Mixtral 8x22b Instruct V0 1 on AMD Instinct MI300X
NVIDIA H200 SXM 141GB
141GB
179.21 tok/s
Price: —
Fit note: higher estimated speed than the baseline option.
Check Mistralai Mixtral 8x22b Instruct V0 1 on NVIDIA H200 SXM 141GB
NVIDIA H100 SXM5 80GB
80GB
128.72 tok/s
Price: —
Fit note: higher estimated speed than the baseline option.
Check Mistralai Mixtral 8x22b Instruct V0 1 on NVIDIA H100 SXM5 80GB
AMD Instinct MI250X
128GB
124.16 tok/s
Price: —
Fit note: higher estimated speed than the baseline option.
Check Mistralai Mixtral 8x22b Instruct V0 1 on AMD Instinct MI250X
NVIDIA H100 PCIe 80GB
80GB
81.71 tok/s
Price: —
Fit note: higher estimated speed than the baseline option.
Check Mistralai Mixtral 8x22b Instruct V0 1 on NVIDIA H100 PCIe 80GB
Need more VRAM for Mistralai Mixtral 8x22b Instruct V0 1?
Intel Arc A770 16GB is 55GB short. Consider a GPU with 93GB+ VRAM.
Best GPU for 70B Models →Best GPU for Deep Learning →All buying guides →

Compare purchase paths

Direct GPU buy options

Check current pricing links for Intel Arc A770 16GB and similar cards.

Open Intel Arc A770 16GB buy links →
Curated best GPU guides

Use workload-focused recommendations before committing to a purchase.

Browse best GPU guides →
Prebuilt AI systems

Compare complete systems if you want ready-to-run hardware.

Compare prebuilt systems →

Not ready to upgrade?

Your GPU doesn't meet the VRAM requirements. Run Mistralai Mixtral 8x22b Instruct V0 1 on cloud GPU instantly.

Vast.aiFrom $0.20/hr · Pay as you goRent GPU →RunPodFrom $0.30/hr · Secure cloudRent GPU →Lambda LabsFrom $0.50/hr · Enterprise-gradeRent GPU →

More questions

Intel Arc A770 16GB buy options & pricingFull guide for Mistralai Mixtral 8x22b Instruct V0 1Best GPU guides for this modelCompare prebuilt local AI systemsBrowse all model + GPU compatibility checksMistralai Mixtral 8x22b Instruct V0 1 Q4 requirementsMistralai Mixtral 8x22b Instruct V0 1 Q4_K_M requirementsCan AMD Instinct MI300X run Mistralai Mixtral 8x22b Instruct V0 1?Can NVIDIA H200 SXM 141GB run Mistralai Mixtral 8x22b Instruct V0 1?Can NVIDIA H100 SXM5 80GB run Mistralai Mixtral 8x22b Instruct V0 1?

Compatibility FAQ

Can Intel Arc A770 16GB run Mistralai Mixtral 8x22b Instruct V0 1?

Intel Arc A770 16GB is not a comfortable Q4 fit for Mistralai Mixtral 8x22b Instruct V0 1 (about 71GB needed).

How much VRAM is needed for Mistralai Mixtral 8x22b Instruct V0 1 on Intel Arc A770 16GB?

Q4 inference is estimated to need about 71GB VRAM on this page, while Intel Arc A770 16GB has 16GB available.

What if Intel Arc A770 16GB is not enough for Mistralai Mixtral 8x22b Instruct V0 1?

Try lower-bit quantization, choose a smaller model, or move to a higher-VRAM GPU from the alternatives list.