HN

Comments (71)

• Menu

  _boffin_
  This just a quantized version of 3.8 next flash on strata that’s branded?
• Menu

  mikeshi42
  > Sharing matrices substantially reduces the weights that must be stored and moved while keeping the expert count unchanged. Each group of 64 experts shares two large matrices, while each expert retains a small set of parameters that captures its differences.145B parameters with only peak 29GB memory usage - really impressive, truly something you can actually run on a decent spec MBP
• Menu

  SwellJoe
  I'm really impressed with the Blender examples. It's amazing how far "tool use" has come, when it now means using a tool as complicated as Blender to perform work that would take a human days to complete. I'm a little skeptical the actual models are workable, in the sense that a human could come in after and manually refine and apply better textures, etc. Historically, agent-made designs are messy as hell, and by the time you clean them up, you haven't saved any time. But, that's begun to get better; the best models are now very good at making clean shape-based SVGs, for example, that are no messier than what a human would make in Inkscape or Illustrator. But, I'll definitely give it a try.
• Menu

  mortalapeman
  Is this a derived from flash next? That's the impression I get from reading over everything. Using Strata + Qwen 3.8 Flash Next now and I am beyond impressed. It's basically as capable as 5.6 Luna in my hands so far. If this is an upgrade I can't wait to try it out.
• Menu

  utopiah
  > Runs on a compatible personal laptop, such as a MacBook ProI'm curious, do normal people (so not HN professional developers or entrepreneurs) have that, as actually personal device (not from their tech company)?I imagine some might have but I feel, and that's me so I'm asking the broader community here, that the average PC user has at best a gaming rig, but that's already a minority, and a lot more often a low end laptop with 16GB of normal RAM, not unified or VRAM. Am I out of touch?
• Menu

  PaulKeeble
  Thy have shipped this as NVFP4 so its Nvidia blackwell only, presumably their inference engine doesn't support anything outside CUDA 13 specified either. Will be interesting to see if this gains some other quants and other inference engines pick it up and we get some standard GGUF files, its a bit of weird release at the moment rather than GGUF file downloads the variants link on HF is leading to a directory of stuff which contains the model spread across a variety of files.
• d--b
  This looks promising, but the comparison to Opus 4.6 on old benchmarks is outdated
• thecopy
  The page is extremely verbose and its difficult for me to scan the page to find the kernels of specificity im looking for.
• Menu

  nico
  It's amazing the level of optimizations we are discovering. At this rate, I wouldn't be surprised if the trend starts reversing, ie. instead of releasing bigger and bigger models, companies start releasing smaller, more capable, specialized models for specific applicationsOver the past few weeks, I've been putting together a small, 6.5M param model. It is conversational, does tool calling, RAG, mathematical modeling/calculations, basic physical simulations, and multi-step chained reasoning. It's still very much _not_ a frontier model. But it already does more than I could get a qwen 2.5 0.5b param model to do with finetuning just 1 year agoMost of the improvements come from being able to direct claude to apply different ideas from recent research that keep coming out. AI labs seem to be focused on 1B+ models, so not much comes out about small models, but many of the things being discovered in research with billion+ model, are adaptable to small ones as well
• Menu

  bob1029
  Frontier AI capabilities also include practical token rates. My current workload would require around 300 tokens/s continuously looking at the last 30 days of token spend. More realistic would be 1500-2000/s for human in the loop activities. I can't babysit the thing 24/7.How far are we from this kind of throughput with local models?
• igleria
  testing is believing! I'll see if I can report back this night.5800X3D + 32 DDR4 GB RAM + AMD 7800 XT 16 GB.Specially interested in the blender usage.edit: ah, just read a bit more. seems it will be a waste of my time given the reqs?
• Menu

  dpweb
  Harness improvements like context pruning, malformed tool call healing also very helpful to boost smaller local models. Doing alot of work in this area lately. Qwen 27B in Terminal Bench 2.1 73->85 for instance.
• rybosome
  TerminalBench scores often correspond to real world performance for coding agents that rely heavily on bash.This score is roughly on par with 5.6 Terra max, which in my direct experience is perfectly capable of driving a cloud agent harness that can do pretty complex knowledge work.Definitely worth an evaluation!
• Menu

  phillennium
  Has anyone figured out the macOS situation with this? The blog post mentions Mac repeatedly, saying things like "day-one support covers macOS". But the released stuff so far seems to be CUDA only. I see no info on when and if the actual Mac support is coming.This weird approach is frustrating, because the actual promise sounds very intriguing, so I'd very much like to test this out.
• Menu

  40four
  I’m admittedly not an expert, I’ve not had the time or energy to try out many of these new American open weight models.I’ll just say this, we obviously all know they (American open weight models) are playing catch-up to the competition. So if your reaction is “why would I use this over Qwen this, or Deepseek that” you’re really missing the mark.Yeah, they are all going to be behind on benchmarks for now. Nobody realistically expects some American open weight model to come out of nowhere and beat Qwen/ Deepseek/ et cetera. But there has been a flurry of new releases from this segment, and it’s interesting to me to watch how it develops.
• paulhart
  Are there any iOS apps that support the Edge0-35B model? I'm curious to try that out on-device.
• Aurornis
  The GitHub repo has more actual details: https://github.com/Edge0-AI/Edge0Based on Qwen3.8-Flash-Next and Strata. They made some interesting tweaks and did some fine tuning on the model, but it's interesting how much marketing speak was layered on their website to hide this fact.It's not at all unusual for people to fine tune models, tweak them, and fork inference engines. It's highly encouraged and appreciated in the community. What is unusual is seeing someone wrap this all up in extensive branding and publish it online as a company.As with all fine-tunes, I'd be a little skeptical of the improved benchmark numbers until people actually use it more. It's really easy to take off the shelf models and fine tune them to get slightly higher benchmark scores without really improving them for normal use. HuggingFace is full of fine tunes that advertise amazing results on specific benchmarks but are worse than the base model when you use them for real work.
• daemonologist
  I am once again impressed by the ability of language models to generate huge amounts of relevant-looking text (and diagrams now!) while actually communicating as little as possible.
• SillyUsername
  For those of us with slow SSDs but a lot of RAM (relative to this model's file size) would this benefit from the extra memory, loading all in, or would I need to set up an old school RAM disk to prevent the swapping?
• fesoliveira
  Interesting, if 3rd party testing and benchmarking hold the published values this is very exciting. I am a bit skeptical given the model size, but I hope it turns out to be true!
• blobinabottle
  Slop article? Saying it works on mac but nothing on the repo to run it without CUDA.
• Menu

  Zetaphor
  This is not open source, this is open weights
• Menu

  quicklywilliam
  This smells off.
• 1612elphi
  I'm really glad they provided us with the graph of "Model Parameters over time", fucking lmao
• suthakamal
  Why so little information about the company on the corporate website?
• nightdeployboy
  Is the era of one seat per person AI coming?
• Menu

  Centigonal
  What's the point of the 120B model?
• speedupagi
  [dead]
• mentalgear
  [flagged]
• ElenaDaibunny
  [flagged]
• devmor
  > Edge0-145B requires a compatible laptop with...Damn, guess I can't run this on my desktop. /s
• dyyd3333
  Ok buddy