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V4.1 Flash model on a consumer GPU with a local serving stack
A author's report on running a V4.1 Flash model locally on a consumer GPU at about 20 tokens per second, with the API layer separated from the inference engine. The speed figures and the claim of no quality loss are the author's own, with no independent evaluation.
The report describes running a language model from the V4.1 Flash series on a consumer RTX 3090 graphics card with 64 GB of system RAM, reaching about 20 tokens per second. The author states there was no quality loss, but this claim is not accompanied by independent evaluation or by metrics published in the text. The stack described separates two parts: a serving frontend responsible for scheduling, tool calling and APIs compatible with OpenAI and Anthropic, and a replaceable forward pass engine, identified in the text as ExLlamaV3.
The finding is useful as an architecture reference, since it shows that local serving on consumer GPUs can separate the API layer from the inference layer. This report does not describe a Rota Nacional feature. To verify it, consult the original text using the title and date given, check the hardware configuration and performance numbers, and test quality with your own evaluation sets. If you use AI to study this material, do not paste personal data, credentials or real prompt excerpts from your organization into it.