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Do AI companies make release plans based on upcoming other models like this? I would think all the processes that go into the repository and weight infrastruct

by mycall 2mo ago

Do AI companies make release plans based on upcoming other models like this? I would think all the processes that go into the repository and weight infrastructure pre-training, checkpointing, knowledge distillation, model compression, post training pipeline, ecosystem integrations, inference API, benchmarking, human eval/safety/alignment, docs, etc... all that dictates the release schedule.

echelon 2mo ago
There has been a long history of AI model releases made shortly before or after a major planned release by another company. Almost always to upstage or steal thunder. Just recently, Minimax H3 released as open weights on the eve of Seedance 2.5 global availability. It's not as good, but it's good enough and it's completely open. Flux 3, which is nowhere near as good as either, suddenly announced their release once news of these other two became public. They knew if they waited they'd be ignored. It didn't really help them much, unfortunately. The LLM releases are even more rivalrous. And don't forget all of the competing launches planned before Google IO or major release events. Companies like to eat into the news and press cycle of their rivals.
- Sabinus 2mo ago
  I've seen it here on HN (it's particularly noticeable via the /active page) multiple times. If Google, OpenAI or Anthropic release something significant, odds are good you'll see a headline from one of the others.
- Forgeties79 2mo ago
  >long history Seems a bit premature of a statement lol
  - echelon 2mo ago
    If you start counting since WaveNet or BERT, it's been ages. Especially when it feels like decades of advancements happen every single year, and rival labs are always trying to one up each other.
    - Forgeties79 2mo ago
      I don’t start counting since we WaveNet or BERT so there you go! Even if I did, we’re talking barely a decade
- vunderba 2mo ago
  BFL is in a rough spot here too. It’s pretty much looking like a repeat of the exact same situation they had when they released Flux2 at the same time Z Image Turbo came out and completely overshadowed their launch. Minimax H3 can run exceptionally fast (10 minutes for a 15 second 0.5mp video and that's stock cuda 13), works on 16 GB VRAM GPUs, etc. If Flux3 is anything like Flux2, it’s going to require an absolute monster truck of a machine and still run significantly slower. Even if it’s a better model, that won’t matter as much if nobody releases any LoRAs or fine-tunes for it. Not to mention BFL licensing often feels deceptively confusing and restrictive.
michimagdesign 2mo ago
Yes, not every model release is reactionary to other labs. Either they had hints for the release of other models or they cut efforts in late stage testing of the models to hit these earlier release dates. There’s always some flexibility. And there’s certainly the incentive to cannibalize the news cycles for competitor models.
- skohan 2mo ago
  I could imagine pulling out all the stops to get a release over the finish line a week early if you're worried about being surpassed by another release
stogot 2mo ago
the last few items there (benchmarking, human evaluation, docs) can be rushed or skipped by leadership if they want to beat comp. they probably spend a few weeks on those things normally
- dannyw 2mo ago
  One window that can be shortened is working with software ecosystem and upstream partners; think day 0 on together, fireworks, Unsloth, etc. That obviously happens from partners getting embargoed weights early.
pu_pe 2mo ago
Yeah but you can probably have everything ready and then accelerate as necessary. Meta itself did this when releasing Llama 4, it was a really botched release right when they were feeling the heat from DeepSeek and others.
drob518 2mo ago
Any company working in a competitive industry is generally aware of what their competitors are doing. PR is an important aspect to market success, so it factors into release schedule. It may not be the dominant factor given engineering constraints, but yea, it’s certainly a factor, and a large one at that.
- Bayien 2mo ago
  [dead]
overfeed 2mo ago
> ...all that dictates the release schedule. AI companies release models when they are ready - not on a set schedule. The steps are required to produce a release candidate, so a company can choose to bless the RC with the best metrics at any time - or alternatively continue (post/)training newer RCs if they feel they can do better, and they have time. When a model is ready for release is subjective, and can take into consideration what the competition is doing. An obvious counter-example to schedules driving releases is the still unreleased Gemini 3.6 Pro.

by mycall 2mo ago

echelon 2mo ago

There has been a long history of AI model releases made shortly before or after a major planned release by another company. Almost always to upstage or steal thunder. Just recently, Minimax H3 released as open weights on the eve of Seedance 2.5 global availability. It's not as good, but it's good enough and it's completely open. Flux 3, which is nowhere near as good as either, suddenly announced their release once news of these other two became public. They knew if they waited they'd be ignored. It didn't really help them much, unfortunately. The LLM releases are even more rivalrous. And don't forget all of the competing launches planned before Google IO or major release events. Companies like to eat into the news and press cycle of their rivals.

Sabinus 2mo ago
I've seen it here on HN (it's particularly noticeable via the /active page) multiple times. If Google, OpenAI or Anthropic release something significant, odds are good you'll see a headline from one of the others.
Forgeties79 2mo ago
>long history Seems a bit premature of a statement lol
- echelon 2mo ago
  If you start counting since WaveNet or BERT, it's been ages. Especially when it feels like decades of advancements happen every single year, and rival labs are always trying to one up each other.
  - Forgeties79 2mo ago
    I don’t start counting since we WaveNet or BERT so there you go! Even if I did, we’re talking barely a decade
vunderba 2mo ago
BFL is in a rough spot here too. It’s pretty much looking like a repeat of the exact same situation they had when they released Flux2 at the same time Z Image Turbo came out and completely overshadowed their launch. Minimax H3 can run exceptionally fast (10 minutes for a 15 second 0.5mp video and that's stock cuda 13), works on 16 GB VRAM GPUs, etc. If Flux3 is anything like Flux2, it’s going to require an absolute monster truck of a machine and still run significantly slower. Even if it’s a better model, that won’t matter as much if nobody releases any LoRAs or fine-tunes for it. Not to mention BFL licensing often feels deceptively confusing and restrictive.

michimagdesign 2mo ago

Yes, not every model release is reactionary to other labs. Either they had hints for the release of other models or they cut efforts in late stage testing of the models to hit these earlier release dates. There’s always some flexibility. And there’s certainly the incentive to cannibalize the news cycles for competitor models.

skohan 2mo ago
I could imagine pulling out all the stops to get a release over the finish line a week early if you're worried about being surpassed by another release

stogot 2mo ago

the last few items there (benchmarking, human evaluation, docs) can be rushed or skipped by leadership if they want to beat comp. they probably spend a few weeks on those things normally

dannyw 2mo ago
One window that can be shortened is working with software ecosystem and upstream partners; think day 0 on together, fireworks, Unsloth, etc. That obviously happens from partners getting embargoed weights early.

pu_pe 2mo ago

Yeah but you can probably have everything ready and then accelerate as necessary. Meta itself did this when releasing Llama 4, it was a really botched release right when they were feeling the heat from DeepSeek and others.

drob518 2mo ago

Any company working in a competitive industry is generally aware of what their competitors are doing. PR is an important aspect to market success, so it factors into release schedule. It may not be the dominant factor given engineering constraints, but yea, it’s certainly a factor, and a large one at that.

Bayien 2mo ago
[dead]

overfeed 2mo ago

> ...all that dictates the release schedule. AI companies release models when they are ready - not on a set schedule. The steps are required to produce a release candidate, so a company can choose to bless the RC with the best metrics at any time - or alternatively continue (post/)training newer RCs if they feel they can do better, and they have time. When a model is ready for release is subjective, and can take into consideration what the competition is doing. An obvious counter-example to schedules driving releases is the still unreleased Gemini 3.6 Pro.