Can the RTX 5090 run dolphin-2.9.1-yi-1.5-34b?

Yes. dolphin-2.9.1-yi-1.5-34b fits the RTX 5090's 32 GB at Q4_K_M (about 21.8 GB needed), running at an estimated 51 tok/s. There's room for up to Q5_K_M if you want higher quality.

VRAM
32 GB
Needs at Q4
21.8 GB
Headroom
10.2 GB
Speed (Q4_K_M)
~51 tok/s

Every quantization

dolphin-2.9.1-yi-1.5-34b (34.4B) on 32 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M20 GB21.8 GBFits~51 tok/s
Q5_K_M24 GB25.8 GBFits~43 tok/s
Q8_037 GB38.8 GBToo big -
FP1669 GB70.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 5090's 1792 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf mradermacher/dolphin-2.9.1-yi-1.5-34b-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full dolphin-2.9.1-yi-1.5-34b details →

Compare

Same model, other hardware - and other models on this card

dolphin-2.9.1-yi-1.5-34b on other hardware

Also runs on the RTX 5090

Frequently asked

Quick answers

Can the NVIDIA RTX 5090 run dolphin-2.9.1-yi-1.5-34b?

Yes. dolphin-2.9.1-yi-1.5-34b fits the RTX 5090's 32 GB at Q4_K_M (about 21.8 GB needed), running at an estimated 51 tok/s. There's room for up to Q5_K_M if you want higher quality.

How much VRAM does dolphin-2.9.1-yi-1.5-34b need?

About 20 GB of weights at Q4_K_M, 37 GB at Q8_0 and 69 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is dolphin-2.9.1-yi-1.5-34b on the RTX 5090?

Roughly 51 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 5090's 1792 GB/s memory bandwidth.