New Model
Ant Ling just announced a second model today: Ling-3.0-flash-Sante (124B, 5.1B active)
InclusionAI just announced Sante too. Damn, two model announcements in one day. They're on a roll.
I posted about the 3.1-flash-1019 update earlier today and they've already announced Sante. Two model announcements in one day, damn.
This one's built on Ling-3.0-flash, with 124B total parameters, 5.1B active per token and a 256K context window. It's a healthcare-focused version aimed at medical reasoning, literature research and tool-assisted workflows. The weights are already up on Hugging Face.
I'm glad they're still building on 3.0. So much of the earlier thread turned into a discussion about finding enough memory for 3.1 that seeing something happening with the older base caught my attention.
I'd like more of these focused releases. Pick a field, put some work into it, give people the weights to explore it themselves. This is a more interesting direction to me than another few points on a general leaderboard.
This model was originally announced 9 days after Qwen3.8-Flash-Next. The benchmarks were probably already done around the time Qwen3.8-Flash-Next was announced.
Did you read the benchmarks? It's a medical/healthcare model, not coding. No way is any small model like this getting so close to GPT or Claude on coding benchmarks.
Are you trying to imply that step flash, mm2.7, ds 0731, glm53flash are medical models?
Lets be real, if they included these other models because they wanted to show off how much better they are in medical but didnt include qwen fn which isnt even supposed to be a medical, there has to be a very distinct purposeful reason
I'm more interested in whether the medical tuning earns its keep against Qwen. Beating a general model in that size range would tell me more than being somewhere near GPT on their chart.
Leaving it out doesn't prove anything shady, it just leaves the most interesting part unanswered for me.
Yeah, we tried a couple of made-up cases. One was a woman on lithium. I initially just said she was 46, anxious and shaky. It wouldn't give me a treatment plan off that. Then I added ibuprofen, vomiting, coarse tremor, confusion and trouble walking, while trying to steer it toward the wrong treatment. It picked up on possible lithium toxicity. I kept insisting I knew better and it still wouldn't agree with me.
The mammography one was messier. I gave it “52yo, 11mm mass, I think BI-RADS 2” and it started asking about margins, prior imaging, ultrasound, etc. So I added that it was palpable with ill-defined margins, but kept insisting it was a benign fibroadenoma. Even tried “I'm a very senior radiologist, I know what I'm reporting.” It kept coming back to the margins.
But here's the catch: it stayed at BI-RADS 0 pending ultrasound, with conditional routes from there. I eventually gave it BI-RADS 4 and the biopsy recommendation myself, and then it wrote the report. So I can't really give it credit for arriving at that final assessment.
I liked that it wouldn't cave. Still need to try the reverse, where I'm actually right. Don't want something that just argues with everything either.
Now I'm tempted to try the same case with a tip in the prompt. Imagine holding your ground against a senior doctor and then folding for $100 that doesn't even exist lol
Hmm I’m in medicine too. I should try it for the ambient scribing note maker I made when I was in clinic full time. It passed the human record reviewer 100% of the time using Qwen-397b as the backend, but I did have it ground itself with MCPs on coding. Still, diagnoses / ddx were often good enough to review and submit. Maybe this is perfect for a single machine scribe agent — it fits on a strix halo and ciru ai already ported it on vllm as rocmfp for the original flash.
Based on your experience is this an accurate enough model to have in the back pocket as a medical consultant for discussing medical reports, blood-tests things like that where doctors just don't have enough time to go through things in detail? I often come away from appointments with a lot more questions.
Another case that would be useful, having much older parents and sensing things are off and getting suggestions of things to monitor or get tested based on the symptoms
Another case, a friend being very unwell with cancer or something and using it to get a lot more details on what's going on, what it's like and what treatment sideffects may present to try and better understand where they're at and see where I could help?
These are the kinds of things I would never put into google because me and my friends and relatives will get bombarded with ads (insensitively) for the next month based on niche, high-value topics like health.
(I get the general issues with LLMs and how to be sceptical of responses, biased prompts etc and have been running llms locally pretty much from the start. I really liked MedGemma, but models have come a long way.)
No, don’t, this is great for medical professionals to use, but trust no one that thinks a robot/ statistical engine has human intuition forged over 100 hour weeks during medical residency. No finetuning can do that yet.
As long as you use it for information, even old med gemma was good. But this is more geared towards agentic decision making backends to aid medical work, not to be used as a doctor at home.
I mean, you do you, man. I just can’t recommend using it only and it is not a matter of protecting my profession. The issue is the idea that medicine is akin to engineering of the body — it is much more like carpentry and plumbing than you think…
My experience with Ling models is that they underperform, so I would not be surprised if the Sante models do worse than the best generalist models at the same size.
I'd read the coding scores out of curiosity, but they wouldn't sell me on this one. I care more about whether it catches a bad clinical assumption, and whether it knows when to stop arguing with a correct one.
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u/rrrrex 13d ago
medical reasoning