• 10 months

    So can a lot of other models.

    “This load can be towed by a single vehicle”

    • 10 months

      the Chinese AI lab also released a smaller, “distilled” version of its new R1, DeepSeek-R1-0528-Qwen3-8B, that DeepSeek claims beats comparably sized models on certain benchmarks

      Most models come in 1B, 7-8B, 12-14B, and 27+B parameter variants. According to the docs, they benchmarked the 8B model using an NVIDIA H20 (96 GB VRAM) and got between 144-1198 tokens/sec. Most consumer GPUs probably aren’t going to be able to keep up with

      • 10 months

        It proved sqrt(2) irrational with 40tps on a 3090 here. The 32b R1 did it with 32tps but it thought a lot longer.

        • 10 months

          On my Mac mini running LM Studio, it managed 1702 tokens at 17.19 tok/sec and thought for 1 minute. If accurate, high-performance models were more able to run on consumer hardware, I would use my 3060 as a dedicated inference device

      • Depends on the quantization.

        7B is small enough to run it in FP8 or a Marlin quant with SGLang/VLLM/TensorRT, so you can probably get very close to the H20 on a 3090 or 4090 (or even a 3060) and you know a little Docker.

    • it’s distilled so it’s going to be smaller than any non distilled of the same quality

    • I’m genuinely curious what you do that a 7b model is “trash” to you? Like yeah sure a gippity now tends to beat out a mistral 7b but I’m pretty happy with my mistral most of the time if I ever even need ai at all.

    • Yeah idk. I did some work with deepseek early on. I wasn’t impressed.

      HOWEVER…

      Some other things they’ve developed like deepsite, holy shit impressive.

    • 9 months

      The censorship only exists on the version they host, which is fair enough. If they’re running it themselves in China, they can’t just break the law.

      If you run it yourself, the censorship isn’t there.

      • 9 months

        Untrue, I downloaded the vanilla version and it’s hardcoded in.

      • 9 months

        Yeah, i think the censoring in the LLM data itself would be pretty vulnerable to circumvention.

      • if the model is censored… then what, retraining it? Or doing it from scratch like what open-r1 is doing?

      • 9 months

        The self hosted model has hard coded censored content.