I 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.
Asked[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?
I think they did work with a few state governments and defence entities. So something like micro-Anthropic X Palantir.
I 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!
I 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
These look like good results for a first model release. I’m hoping to see more, especially in the 30b parameter range.
I 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.
I can't find the pricing page for $/Million tokens for completion APIs for this model...Anyone knows where it is?
I 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
It appears to be free (like their old Sarvam-M).
great izzat to the nation
Got 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
> These guys did not even bother with an official huggingface space
I do think convincing world-class talent to live in Bangalore is likely to be a challenge though.
Indians deep-down often aren't comfortable in the West given the subtle racism and general social-rejection (last year's anti-Indian hate on X remains fresh in memory).
BLR has of late become a sort of "refuge" of tech retunees (with horrible third-world government and infrastructure, though). And it shows - the Matryoshka Embeddings being used in Gemini on-device / embedded models, came out of Deepmind BLR.
For sure, there’s no place like home, and people have families and networks they can’t take with them. Still, getting that Western passport is a draw, and there’s always Abu Dhabi if you want quite close to home and a decent biryani, but also want world-class infrastructure and high (although not quite US) wages
Bigger issue here is why the government is involved with select companies for subsidizing compute. There’s no pre or post criterion to assess success, it should have just been an open market for people with money to purchase compute instead of 10 companies with no prior experience in making models of any kind.
Public funds should beget public datasets and training scripts to see how it is being aligned as well and not just pandering to a particular govt.
> Bigger issue here is why the government is involved with select companies for subsidizing compute.
Government-choosing-winners has worked much better, in many such cases, than free-market absolutists would have you believe…
I 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.
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.
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-hardwar...
I 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.
Asked[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
I think they did work with a few state governments and defence entities. So something like micro-Anthropic X Palantir.
I 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!
I 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
These look like good results for a first model release. I’m hoping to see more, especially in the 30b parameter range.
I 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.
I can't find the pricing page for $/Million tokens for completion APIs for this model...Anyone knows where it is?
I 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
It appears to be free (like their old Sarvam-M).
great izzat to the nation
Got 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
> These guys did not even bother with an official huggingface space
https://huggingface.co/sarvamai
That is their profile not a HF Space
Got to start somewhere.
I do think convincing world-class talent to live in Bangalore is likely to be a challenge though.
Indians deep-down often aren't comfortable in the West given the subtle racism and general social-rejection (last year's anti-Indian hate on X remains fresh in memory).
BLR has of late become a sort of "refuge" of tech retunees (with horrible third-world government and infrastructure, though). And it shows - the Matryoshka Embeddings being used in Gemini on-device / embedded models, came out of Deepmind BLR.
For sure, there’s no place like home, and people have families and networks they can’t take with them. Still, getting that Western passport is a draw, and there’s always Abu Dhabi if you want quite close to home and a decent biryani, but also want world-class infrastructure and high (although not quite US) wages
Bigger issue here is why the government is involved with select companies for subsidizing compute. There’s no pre or post criterion to assess success, it should have just been an open market for people with money to purchase compute instead of 10 companies with no prior experience in making models of any kind.
Public funds should beget public datasets and training scripts to see how it is being aligned as well and not just pandering to a particular govt.
> Bigger issue here is why the government is involved with select companies for subsidizing compute.
Government-choosing-winners has worked much better, in many such cases, than free-market absolutists would have you believe…
I 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
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.
[flagged]
https://nohello.net
saarvam
[flagged]
Or if you can ask it your doubts?
You must consider yourself so clever.
AI: Artificial Indian.
[flagged]
It'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/
Another user linked to the discussion that post had already: 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-hardwar...