llamaperf

NVIDIA RTX 3090 vs NVIDIA V100 32GB for local LLMs

217 reports on the NVIDIA RTX 3090 and 27 on the NVIDIA V100 32GB

Which is faster for local LLMs?

On Qwen3.8 27B at 4-bit, the NVIDIA RTX 3090 has 38.4 generation tokens/s (5 runs); prompt processing 561.0 tokens/s (2 runs); the NVIDIA V100 32GB has 31.4 generation tokens/s (2 runs); prompt processing 940.5 tokens/s (2 runs). Those are community reports whose engines and settings differ, so the gap is a rough sign, not a controlled measure of the two cards. Memory bandwidth, which caps how fast a card can write, is about the same on both (936 GB/s on the NVIDIA RTX 3090, 900 on the NVIDIA V100 32GB). Across 2 shared models with generation measurements on both cards, the NVIDIA RTX 3090's median is higher on 2 and the NVIDIA V100 32GB's on 0.

NVIDIA RTX 3090
Memory
24GB
Memory bandwidth
936 GB/s
FP16 compute
142 TFLOPS
Reports
217
NVIDIA V100 32GB
Memory
32GB
Memory bandwidth
900 GB/s
FP16 compute
125 TFLOPS
Reports
27

Measured on both

Generation and prompt processing speeds from plain runs (one device, one request, no speculative decoding, the whole model in the device's memory) of the same model size at the same bit class. Each side shows the engines and reported context behind its median. Context can mean a configured window or prompt depth, so these are community comparisons with differing settings. How to read these

ModelNVIDIA RTX 3090NVIDIA V100 32GB
Qwen3.8 27B4-bit38.45 runsPP 561.0 (2 runs)llama.cpp, vLLM128K to 256K context, 1 not stated31.42 runsPP 940.5 (2 runs)llama.cpp, 1 not stated32K to 128K context
Qwen3.6 27B4-bit42.0one runPP 1020.0 (one run)llama.cpp100K context32.2one runllama.cppcontext not stated

Estimated by the calculator

The quant the calculator recommends for each card and its estimated speed at a 32,768-token context with 32 GB of system RAM, from memory bandwidth and the model's shape. Where a model was also measured above, the measurement wins.

ModelNVIDIA RTX 3090NVIDIA V100 32GB
Qwen3.8 27B33.9 t/sQ4_K_M22.6 t/sQ6_K
Qwen3.6 27B33.9 t/sQ4_K_M22.6 t/sQ6_K
Qwen3.8 125B · 6B active19.4 t/sQ2_K, experts in RAM19.4 t/sQ2_K, experts in RAM
Qwen3.6 35B · 3B active120.1 t/sQ4_K_S81.9 t/sQ5_K_M
DeepSeek V4 Flash 284B · 13B activedoesn't fit at these settingsdoesn't fit at these settings
Gemma 4 26B · 4B active76.4 t/sQ5_K_S57.5 t/sQ6_K
GLM-5.3 320B · 18B activedoesn't fit at these settingsdoesn't fit at these settings
DeepSeek V4.1 Flash 552B · 16B activedoesn't fit at these settingsdoesn't fit at these settings

Change the context, RAM or model in the calculator: NVIDIA RTX 3090 · NVIDIA V100 32GB

Every report on each card, with its source: NVIDIA RTX 3090 · NVIDIA V100 32GB

More comparisons