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Ollama has been deliberately misrepresenting R1 distill models as "R1" for marketing purposes. A lot of "AI" influencers on social media are unabashedly doing t

Ollama has been deliberately misrepresenting R1 distill models as "R1" for marketing purposes. A lot of "AI" influencers on social media are unabashedly doing the same. Ollama's default "R1" model is a 4-bit RTN quantized 7B model, which is nowhere close to the real R1 (a 671B parameter fp8 MoE). https://www.reddit.com/r/LocalLLaMA/comments/1i8ifxd/ollama_is_confusing_people_by_pretending_that_the/ https://www.reddit.com/r/LocalLLaMA/comments/1i8ifxd/ollama_...

wklauss 2y ago
Ollama is pretty clear about it, it's not like they are trying to deceive. You can also download the 671B model with Ollama, if you like.
- woadwarrior01 2y ago
  Yeah, they're so clear in fact that they call the distilled models "R1" in the url and everywhere on the page[1], instead of using the "DeepSeek-R1-Distill-" prefix, as DeepSeek themselves do[2]. [1]: https://ollama.com/library/deepseek-r1 https://ollama.com/library/deepseek-r1 [2]: https://github.com/deepseek-ai/DeepSeek-R1#deepseek-r1-distill-models https://github.com/deepseek-ai/DeepSeek-R1#deepseek-r1-disti...
- whimsicalism 2y ago
  no they are not, they intentionally remove every reference to this not being r1 from the cli and changed the names from the ones both Deepseek and Huggingface used.
  - nyrikki 2y ago
    They used short strings for the names, which is very different from deception. https://ollama.com/search https://ollama.com/search > DeepSeek's first-generation of reasoning models with comparable performance to OpenAI-o1, including six dense models distilled from DeepSeek-R1 based on Llama and Qwen. Well I guess if you are in the Enterprise Java naming model you would expect something like "VisitorModelUtilsListGetterAdapterInterceptorMessageManagerDrivenObserverPool" If you look at their API docs you will see: model: name of the model to push in the form of <namespace>/<model>:<tag> I don't think there is any reason to jump to the conclusion it is some type of conspiracy here, just naming things based on a API that probably didn't think about distillation when they created it.
  - blacklightpy 2y ago
    Yet, I did not see a single issue made on the GitHub repository, and I just made one myself (https://github.com/ollama/ollama/issues/8698 https://github.com/ollama/ollama/issues/8698).
horsawlarway 2y ago
I mean... yes. The DeepSeek announcement puts R1 right there in the name for those models. https://api-docs.deepseek.com/news/news250120 https://api-docs.deepseek.com/news/news250120 It's fairly clear that R1-Llama or R1-Qwen is a distill, and they're all coming directly from DeepSeek. As an aside, at least the larger distilled models (I'm mostly running r1-llama-distill-70b) are definitely not the same thing as the base llama/qwen models. I'm getting better results locally, admittedly with the slower inference time as it does the whole "<think>" section. Surprisingly - The content in the <think> section is actually quite useful on its own. If you're using the model to spitball or brainstorm, getting to see it do that process is just flat out useful. Sometimes more-so than the actual answer it finally produces.

wklauss 2y ago

Ollama is pretty clear about it, it's not like they are trying to deceive. You can also download the 671B model with Ollama, if you like.

woadwarrior01 2y ago
Yeah, they're so clear in fact that they call the distilled models "R1" in the url and everywhere on the page[1], instead of using the "DeepSeek-R1-Distill-" prefix, as DeepSeek themselves do[2]. [1]: https://ollama.com/library/deepseek-r1 https://ollama.com/library/deepseek-r1 [2]: https://github.com/deepseek-ai/DeepSeek-R1#deepseek-r1-distill-models https://github.com/deepseek-ai/DeepSeek-R1#deepseek-r1-disti...
whimsicalism 2y ago
no they are not, they intentionally remove every reference to this not being r1 from the cli and changed the names from the ones both Deepseek and Huggingface used.
- nyrikki 2y ago
  They used short strings for the names, which is very different from deception. https://ollama.com/search https://ollama.com/search > DeepSeek's first-generation of reasoning models with comparable performance to OpenAI-o1, including six dense models distilled from DeepSeek-R1 based on Llama and Qwen. Well I guess if you are in the Enterprise Java naming model you would expect something like "VisitorModelUtilsListGetterAdapterInterceptorMessageManagerDrivenObserverPool" If you look at their API docs you will see: model: name of the model to push in the form of <namespace>/<model>:<tag> I don't think there is any reason to jump to the conclusion it is some type of conspiracy here, just naming things based on a API that probably didn't think about distillation when they created it.
- blacklightpy 2y ago
  Yet, I did not see a single issue made on the GitHub repository, and I just made one myself (https://github.com/ollama/ollama/issues/8698 https://github.com/ollama/ollama/issues/8698).

horsawlarway 2y ago

I mean... yes. The DeepSeek announcement puts R1 right there in the name for those models. https://api-docs.deepseek.com/news/news250120 https://api-docs.deepseek.com/news/news250120 It's fairly clear that R1-Llama or R1-Qwen is a distill, and they're all coming directly from DeepSeek. As an aside, at least the larger distilled models (I'm mostly running r1-llama-distill-70b) are definitely not the same thing as the base llama/qwen models. I'm getting better results locally, admittedly with the slower inference time as it does the whole "<think>" section. Surprisingly - The content in the <think> section is actually quite useful on its own. If you're using the model to spitball or brainstorm, getting to see it do that process is just flat out useful. Sometimes more-so than the actual answer it finally produces.