Can the NVIDIA RTX 5080 run Mixtral 8x7B?

RTX 5080 × Mixtral 8x7B8K context
NoDoes not fit in memory
Memory at Q4_K_M30 GB of 16 GB
Weights 28.3 GBKV cache 1.1 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, Mixtral 8x7B needs about 30 GB, but the NVIDIA RTX 5080 has 16 GB usable. You could offload some layers to system RAM, but it will be very slow.

Run it on a rented GPU

On a cloud GPU with enough memory, the same command you'd use locally works:

ollama run mixtral:8x7b

At Q4_K_M it needs about 30 GB, so pick a GPU with at least 32 GB.

Run it in the cloud

Too big for the NVIDIA RTX 5080? Run Mixtral 8x7B on a rented GPU instead.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 16 GB the NVIDIA RTX 5080 can use.

QuantQualityMemoryFits?Speed
FP16Full quality95.1 GBToo big—
Q8_0Near-lossless51.3 GBToo big—
Q6_KExcellent40 GBToo big—
Q5_K_MVery good34.9 GBToo big—
Q4_K_MGood, most popular30 GBToo big—
Q3_K_MNoticeably degraded24.5 GBToo big—
Q2_KHeavily degraded19.2 GBToo big—

Frequently asked questions

Can NVIDIA RTX 5080 run Mixtral 8x7B?

No. Even at Q4_K_M, Mixtral 8x7B needs about 30 GB, but the NVIDIA RTX 5080 has 16 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does Mixtral 8x7B need?

About 30 GB at Q4_K_M with 8,192 tokens of context, and about 95.1 GB at full FP16 precision.

How fast is Mixtral 8x7B on the NVIDIA RTX 5080?

It does not fit in the NVIDIA RTX 5080's memory, so most layers would run from system RAM and generation would be very slow.