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Can the NVIDIA RTX 2080 Ti run Phi-3.5 Mini 3.8B?

RTX 2080 Ti × Phi-3.5 Mini 3.8B8K context
YesRuns fully on the GPU
Memory at Q8_07.9 GB of 11 GB
Weights 4.1 GBKV cache 3.2 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Speed~91tokens per second
Max context14Ktokens that fit at Q8_0
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The NVIDIA RTX 2080 Ti can run Phi-3.5 Mini 3.8B fully in VRAM at Q8_0 (near-lossless), using about 7.9 GB of the 11 GB available, at roughly 91 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Phi-3.5 Mini 3.8B:

ollama run phi3.5:3.8b

Ollama's default download is Q4_K_M (about 6.1 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the RTX 2080 Ti

Run it in the cloud

No NVIDIA RTX 2080 Ti? Run Phi-3.5 Mini 3.8B in the cloud.

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

Rent a GPU on RunPodRent a GPU on Vast.ai

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 11 GB the NVIDIA RTX 2080 Ti can use.

QuantQualityMemoryFits?Speed
FP16Full quality11.5 GBToo big—
Q8_0Near-lossless7.9 GBFits~91 tok/s
Q6_KExcellent7 GBFits~118 tok/s
Q5_K_MVery good6.5 GBFits~136 tok/s
Q4_K_MGood, most popular6.1 GBFits~160 tok/s
Q3_K_MNoticeably degraded5.7 GBFits~198 tok/s
Q2_KHeavily degraded5.3 GBFits~258 tok/s

Measured speed from real RTX 2080 Ti owners

Tokens per second that people measured on their own NVIDIA RTX 2080 Ti, next to our estimate.

No one has measured Phi-3.5 Mini 3.8B on the NVIDIA RTX 2080 Ti yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 2080 Ti? Add your real speed

One command times Phi-3.5 Mini 3.8B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- phi3.5:3.8b

Windows (PowerShell)

$env:GPUFIT_MODEL="phi3.5:3.8b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Phi-3.5 Mini 3.8B comfortably

Models that run well on the NVIDIA RTX 2080 Ti

Frequently asked questions

Can NVIDIA RTX 2080 Ti run Phi-3.5 Mini 3.8B?

Yes. The NVIDIA RTX 2080 Ti can run Phi-3.5 Mini 3.8B fully in VRAM at Q8_0 (near-lossless), using about 7.9 GB of the 11 GB available, at roughly 91 tokens/second.

How much VRAM does Phi-3.5 Mini 3.8B need?

About 6.1 GB at Q4_K_M with 8,192 tokens of context, and about 11.5 GB at full FP16 precision.

How fast is Phi-3.5 Mini 3.8B on the NVIDIA RTX 2080 Ti?

Roughly 91 tokens per second at Q8_0, estimated from the NVIDIA RTX 2080 Ti's 616 GB/s memory bandwidth.