Benchmark result
swift-1.5-iq3_xxs on NVIDIA GeForce RTX 5090 — 116.5 tok/s
Measured with llama.cpp Strata 0.1.35 on October 2, 2026.
What the model built
Open full screen →The coding scenario asks for a playable game in a single HTML file. This is exactly what the model returned, unedited; the frame only adds a line that tells this page how tall it is.
How this run compares
swift-1.5-iq3_xxs on other hardware
- 55.5tok/s85.6Advanced Micro Devices, Inc. [AMD/ATI] Raphael +1 more
- 53.2tok/s84.0Advanced Micro Devices, Inc. [AMD/ATI] Raphael +1 more
- 53.0tok/s84.4Advanced Micro Devices, Inc. [AMD/ATI] Raphael +1 more
- 52.7tok/s81.3Advanced Micro Devices, Inc. [AMD/ATI] Raphael +1 more
- 50.8tok/s84.9Advanced Micro Devices, Inc. [AMD/ATI] Raphael +1 more
Reproduce this run
toolllama.cpp Strata 0.1.35
modelswift-1.5-iq3_xxs
context262,144
thinkingon
effortxhigh (model default)
clientv0.4.59+97
Set those in llama.cpp, then:
llm-benchmark benchmark --model "swift-1.5-iq3_xxs" --tool "llama.cpp"The client prompts for context length and thinking mode, and for the KV cache dtype on Unsloth Studio. Sampling is left at the model default — the values above are what the tool reported using, not overrides the client sent.