Can the NVIDIA RTX 3070 run Mistral Small 24B?

RTX 3070 × Mistral Small 24B8K context
NoDoes not fit in memory
Memory at Q4_K_M16.2 GB of 8 GB
Weights 14.3 GBKV cache 1.3 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, Mistral Small 24B needs about 16.2 GB, but the NVIDIA RTX 3070 has 8 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 mistral-small:24b

At Q4_K_M it needs about 16.2 GB, so pick a GPU with at least 24 GB.

Run it in the cloud

Too big for the NVIDIA RTX 3070? Run Mistral Small 24B 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 8 GB the NVIDIA RTX 3070 can use.

QuantQualityMemoryFits?Speed
FP16Full quality49.1 GBToo big—
Q8_0Near-lossless27 GBToo big—
Q6_KExcellent21.3 GBToo big—
Q5_K_MVery good18.7 GBToo big—
Q4_K_MGood, most popular16.2 GBToo big—
Q3_K_MNoticeably degraded13.5 GBToo big—
Q2_KHeavily degraded10.8 GBToo big—

Frequently asked questions

Can NVIDIA RTX 3070 run Mistral Small 24B?

No. Even at Q4_K_M, Mistral Small 24B needs about 16.2 GB, but the NVIDIA RTX 3070 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does Mistral Small 24B need?

About 16.2 GB at Q4_K_M with 8,192 tokens of context, and about 49.1 GB at full FP16 precision.

How fast is Mistral Small 24B on the NVIDIA RTX 3070?

It does not fit in the NVIDIA RTX 3070's memory, so most layers would run from system RAM and generation would be very slow.