Find which open-weight LLMs fit in your GPU or Mac and compare the speeds people report on setups like yours.
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Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.
NVIDIA RTX 3090 · text-generation-webui · 384,000 ctx
User reports DeepSeek-V4-Flash-0731 UD-IQ3_S running under the llama.cpp loader in text-generation-webui. Setup uses --n-cpu-moe 39 to offload MoE experts to system RAM, with the loader estimating roughly 136 GB total and relying on 128 GB of DDR5 at 5600 MHz.
NVIDIA RTX 3090 · text-generation-webui · 16,384 ctx
User reports Qwen3-235B-A22B at about 7.5 t/s generation and about 75k pp on a single RTX 3090 with 128 GB of system RAM. Setup is textgen with batch size 1024, 16384 context, autofit layers, and 38 of 48 threads on a dual Xeon DDR4 system. Generation dips to about 7 t/s at 10k context. The user calls it a daily driver for months for uncensored ERP roleplay, and mentions Step 3.7 Flash as an alternative that is censored and verbose, along with Gemma 4 and MiniMax-M2.5, which were not run.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking