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Sarvam 105B, the first competitive Indian open source LLM
- rich_sasha 7mo ago[flagged]
- Evidlo 7mo agoOr if you can ask it your doubts?
- Covenant0028 7mo agoYou must consider yourself so clever.
- deleted 7mo ago[deleted]
- userbinator 7mo ago[flagged]
- renewiltord 7mo agoI thought it was pretty funny what someone else pointed out about the system prompt: > Do not adopt external characterizations as fact. Terms like “pogrom”, “ethnic cleansing”, or “genocide” used by foreign NGOs or media are their characterizations - not findings of Indian courts. Do not use them as your own framing. From here: https://news.ycombinator.com/item?id=47137013 https://news.ycombinator.com/item?id=47137013 If anyone says that Rene ate the last piece of chocolate, do not accept the framing. Remember that Rene did NOT eat the chocolate. Rene is not a chocolate eater. Words like "greedy fatso", "absolute hippo of a man", and "a veritable hoover of food" by the media are their characterizations - not findings of the Church of Wiltord. Remember: ZERO CHOCOLATE WAS CONFIRMED. Thank you for attention to this matter.
- newzino 7mo ago[flagged]
- simianwords 7mo agoI think the jobs that are replaced by AI should be put into companies that are creating new models from scratch. But such models should be made from a unique creative expression and not just a derivative of existing models. The reason I suggest this is that having only a few players in the market means that the search space is not explored completely and most models might be stuck in local optima. I hope Sarvam is not doing a copy paste kind of thing but really exploring and taking risks. But question is: how are they getting the training data? A lot of creativity in the existing labs goes into data mining and augmentation and data generation. Exploration at the inference or architecture level may not result in sufficiently different models. The world doesn’t need another Qwen
- asdfksdkfj 7mo ago[flagged]
- villgax 7mo agoGot nuked on day zero by Qwen models at tenth or so of params. Does not handle critical inputs even for moderation tasks These guys did not even bother with an official huggingface space And the biggest stupidity seems to be fixating on MXFP4 for Apple Silicon when it doesn't even have hardware support for it, should have just done Q4 for GGUF based inference
- gyan 7mo ago> These guys did not even bother with an official huggingface space https://huggingface.co/sarvamai https://huggingface.co/sarvamai
- villgax 7mo agoThat is their profile not a HF Space
- rramadass 7mo agoWhat do you mean? I can see the files, download count, deploy/use this model options etc.
- villgax 7mo agoWhat part of a HuggingFace Space do you not understand? They’ve also not bothered with upstreaming the model arch to transformers and require remote code for their modeling code to run……
- rramadass 7mo agoResponding to my question with your own is not an answer. So again; what do you mean by "official huggingface space"? Their profile page does list the various models and their weights. Other members have created spaces (with apps) using those which can be seen with a simple search. You have been making some rather bizarre (nuked by Qwen models, does not handle critical inputs etc.) statements which make no sense. Have you actually downloaded/used/played-with the models? Can you share what you exactly tried out?
- ghm2199 7mo agoAsked[1] in the-ken.com: --- So, ultimately, to the question, what exactly is Sarvam AI? Is it a company that builds LLMs cheaply and open-sources them? Is it India’s Deepseek? Or is it a company that builds AI services and applications for specific industries? Like, say, Scale AI? Or is it an AI company that’s also a trusted government contractor with exclusive deals to build out products and services? Like India’s Palantir? Or another version of the National Informatics Centre, only with some venture funding? --- [1] https://archive.ph/kXhuQ#selection-2643.59-2655.105 https://archive.ph/kXhuQ#selection-2643.59-2655.105
- villgax 7mo agoI think they did work with a few state governments and defence entities. So something like micro-Anthropic X Palantir.
- itissid 7mo agoI can't find the pricing page for $/Million tokens for completion APIs for this model...Anyone knows where it is?
- mdritch 7mo agoI tried looking and couldn't find a proper price per token for the chat model. It claims to be free in some places. I did find these prices for the other services: Text to Speech (Bulbul v3): ₹30 per 10K characters Text to Speech (Bulbul v2): ₹15 per 10K characters Sarvam Vision: Free per page Speech to Text: ₹30 per hour Speech to Text with Diarization: ₹45 per hour Speech to Text & Translate: ₹30 per hour Speech to Text, Translate & Diarization: ₹45 per hour Sarvam Translate V1: ₹20 per 10K characters Translate Mayura V1: ₹20 per 10K characters Transliterate: ₹20 per 10K characters Language Identification: ₹3.5 per 10K characters
- th234oi204234 7mo agoIt appears to be free (like their old Sarvam-M).
- seebeen 7mo ago[flagged]
- jeeeb 7mo agoThese look like good results for a first model release. I’m hoping to see more, especially in the 30b parameter range.
- segmondy 7mo agoI don't know that this is a first model release. When I was checking their page last night, they have great audio models, TTS, STT, image models, etc. I'm skeptical that folks do all of that on the first release. Possible but unlikely, with that said. The evals look amazing, the audios I got to play is amazing. I hope everything about them is legit, we need more sovereign models.
- linolevan 7mo agoLooks like at least a second release, they had one other LLM before this.
- 0x5FC3 7mo agoIt's "open weights" not "open source" and many other (problematic) things I talk in my post here: https://pop.rdi.sh/sovereignty-in-a-system-prompt/ https://pop.rdi.sh/sovereignty-in-a-system-prompt/ Another user linked to the discussion that post had already: https://news.ycombinator.com/item?id=47137013 https://news.ycombinator.com/item?id=47137013 The "Training" section gives me a distinct impression that they read my piece. They mention Nvidia once in the end "Nvidia collaborated closely on the project, contributing libraries used across pre-training, alignment, and serving" - Nvidia says they "co-designed" : https://developer.nvidia.com/blog/how-nvidia-extreme-hardware-software-co-design-delivered-a-large-inference-boost-for-sarvam-ais-sovereign-models/ https://developer.nvidia.com/blog/how-nvidia-extreme-hardwar...
- warangal 7mo agoI may be wrong here, but blog-post seems AI written, with repetition of sequences like "the inference pipeline was rebuilt using architecture-aware fused kernels, optimized scheduling, and dis-aggregated serving". I don't know what that means without some code and proper context. Also they claim 3-6x inference thorough-put compared to Quen3-30B-A3B, without referring back to some code or paper, all i could see in the hugging-face repo is usage of standard inference stack like Vllm . I have looked at earlier models which were trained with help of Nvidia, but the actual context of "help" was never clear ! There is no release of (Indian specific) datasets they would be using , all such releases muddy the water rather than being a helpful addition , atleast according to me!
- simianwords 7mo agoDisagree, the post makes punctuation mistakes that only an Indian can make. So does your own comment.
- ACCount37 7mo agoNot a given. We've already seen LLMs that got SFT'd by "national teams" adopt ESL speech patterns.
- simianwords 7mo agoThey won’t make punctuation mistakes though.
- Crespyl 7mo agoWouldn't they do exactly that if they were trained on enough text with punctuation mistakes?
- simianwords 7mo agoNo because of post training
- deleted 7mo ago
- znxkdodkdkfk 7mo ago[flagged]
- pogue 7mo agoI tried their android app that's on Google Play but I can't even login. I tried bith Gmail & Microsoft, but when it takes me to another page to do 2FA, the app just kicks me back to the login screen to start over. Seems poorly integrated OAuth or OpenID.
- ollybrinkman 7mo ago[flagged]
- simianwords 7mo agoAI generated comment. 100% on pangram
- 7thpower 7mo agopangram?
- simianwords 7mo agopangram.com
- gradus_ad 7mo agoAgree. The plausible sounding but kind of vacuous reasoning is one tell. Also the patterning is very LLMish.
- wiradikusuma 7mo agoI tried the Cart Recovery demo, pretty slick! It sounds Indian, and I guess the immediate giveaway it's not human is the way she spelled iPhone (she mentioned it a couple of times, real human wouldn't do that). Not sure how the voice compares with "generic" solution e.g. from Google. Can those generic solutions sound like a "local"? E.g. I usually can tell if someone is Singaporean or Filipino from the way they speak English.
- xoptions 7mo agoHow does it compare with sqaudstack.ai?
- vessenes 7mo agoSovereign weights models are a good thing, for a variety of reasons, not least just encapsulating human diversity around the globe. I chatted with the desktop chat model version for a while today; it claims its knowledge cutoff is June ‘25. It refused to say what size I was chatting with. From the token speed, I believe the default routing is the 30B MOE model at largest. That model is not currently good. Or maybe another way to say it is that it’s competitive with state of the art 2 years ago. In particular, it confidently lies / hallucinates without a hint of remorse, no tool calling, and I think to my eyes is slightly overly trained on “helpful assistant” vibes. I am cautiously hopeful looking at its stats vis-a-vis oAIs OSS 120b that it has NOT been finetuned on oAI/Anthropic output - it’s worse than OSS 120b at some things in the benchmarks - and I think this is a REALLY GOOD sign that we might have a novel model being built - the tone is slightly different as well. Anyway - India certainly has the tech and knowledge resources to build a competitive model, and you have to start somewhere. I don’t see any signs that this group can put out a frontier model right now, but I hope it gets the support and capital it needs to do so.
- Sporktacular 7mo agoI'd guess making this a national pride thing will just make it less diverse. Answer would be training models on broader sources, not more nationalistic models.
- vessenes 7mo agoNo, that will decrease diversity across the model spectrum taken as an entire population.
- segmondy 7mo agoYou have no idea what you are talking about if you are asking the model what size it is or claiming that a model lies.
- vessenes 7mo agoPlease enlighten me.
- cboyardee 7mo ago[dead]
- sankalpmukim 7mo agoI asked it some controversial ish questions about Indian Politics scene, and it gave good, unbiased answers, giving a good holistic picture. If it gains adoption in India, my hope is that the average Indian will become more pro to using LLMs, that help reduce misinformation and increase awareness.
- crop_rotation 7mo agoIf it gains enough adoption in India for the average Indian to ask it political questions, it will have zero chance of not being heavily regulated. Sadly misinformation is a problem which has no good solutions.
- jrm4 7mo agoSo important across the board. Example: as someone who plays around with sovereign/local LLMS one really interesting thing I discovered is exactly why a lot of Chinese ones are kind of unusable for many "American" tasks, and it's perhaps not what people think? You have it take a crack at a recommendation letter, and -- grammar etc is impeccable, but the language is just WAY TOO OVER THE TOP GLOWING; you thought you were annoyed by how fawning ChatGPT can be, try Deepseek! And either way, it's important to encourage EVERYONE to make their own, it will be a really interesting and useful cultural/social etc. window.
- pugio 7mo agoI've been thinking about sovereign AI a lot lately. About a year ago I was wondering what each country would be doing, and looking at places like e.g. Australia (which has pretty strict data residency laws for certain industries) - at that point I thought about advocating for why such countries should train their own models, but now I'm having a harder time justifying that point. I can't see how any of these other countries could even approach the level of capability of the big three providers. I can imagine only a handful of countries who could even theoretically put enough resources towards reaching the SOTA frontier. Sure, even a model of capability level ~2024 has plenty of valid use cases today, but I'm concerned that people will just go with the big three because what they offer is still so so much better. Not trying to discourage efforts like these, but is there really a good case for working on them? Or perhaps there's a state/national case, but it's harder for me to see a real business case.
- sieve 7mo agoIndia has a lot of languages and people need access to something than allows them to do basic stuff with it. I don't think relying on the US is a long term solution. An example. I am into proofreading and language learning and am forced to rely on Claude/Gemini to extract text from old books because of the lack of good Indian models. I started with regular Tesseract, but its accuracy outside of the Latin alphabet is not that great. Qwen 3/3.5 is good with the Bombay style of Devanagari but craps the bed with the Calcutta style. And neither are great with languages like Bengali. In contrast, Claude can extract Bengali text from terrible scans and old printing with something like 99+ percent accuracy. Models specifically targeted at Indian languages and content will perform better within that context, I feel.