People say this about the frontier every time, and the open models catch up in a matter of months every time.

Why does that seem unlikely? The difference between frontier and open weights has been much less than 12 months for a while now.

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Agree, Mercury 3 is one of my favorite models right now...the speed is such a quality of life improvement.

May I add Poolside (Laguna S) to this? Used them extensively during their free trial (sadly now apparently over).-

For my own purposes, I found Mercury Decide to be excellent. Better than Jev at what I threw at it. Inception did a really great job with it.

Really? I'm surprised. What do you use it for?

My read on Diffusion LLMs has been that it's cool tech, but only useful for things like like code autocomplete or editing a block of text.

They don't beat autoregressive models on quality per compute, assuming you are serving lots of users and can batch requests.

Sorry to put it bluntly, but, Mercury is sh*t in comparison. And I have genuinely tried a few times to use it since the speed is so good. But nop.. it just isn't there.

Could you give some examples what makes them good, thanks

> yet still cannot even beat MiniMax M3.1 Flash (220B) despite having 2.7x more parameters

MiniMax M3.1 Flash is 428B total parameters, so the size ratio is more like 1.4x. Model card here: https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash

The number HF calculates from the safetensors metadata is often wrong (e.g. counting u8-packed 4-bit weights as half a weight each) so you need to take the number from the actual model card.

I wouldn't bet on the numbers of compute reported by Chinese labs. Those Singapore Nvidia orders had to go somewhere.

Yes, Mira Murati's Thinking Machines. They are apparently trying to raise $5B at $40B, after raising $2B at $10B last year.

There’s still room to beat Deepseek in communicating clearly and following instructions to the letter (it’s very over-eager imo). I can put it in subagent but for main model, as far as open models go, there’s still no alternative to GLM-5.3 Flash.

(Though to be frank even Sol&Astra have the same problems, and Deepseek is probably heavily "inspired". I guess it may come down to preference though the new Terra 6.1 does very favorably on both of those aspects. I really do prefer to work with it. Wish there was some kind of Terra Super with the same benchmarks as the bigger models.)

In their last technical report (for the original Inkling model), they mentioned 'To bootstrap post-training, we ran an initial SFT on synthetic data generated by open-weights models including Kimi K2.5. The bootstrap accounts for a small fraction of compute, with the majority being employed for large-scale RL on synthetic and human-created environments.' and in their most recent one they said 'The H3 and H4 mixtures consisted mostly of trajectories sampled from earlier models including Kimi K3 and our own models, filtered for correctness and alignment.' So it does seem like traces from larger models do contribute. I think Microsoft is one of the few companies that has actively made an effort to avoid distillation with their MAI series.

Everyone is building on everything that comes before.

Houses are not built from scratch either. The know-how, power, water, roads, materials…

Imagine if Mira Murati and John Schulman actually know what they're doing?

It’s about 2-3X more expensive so about the same token efficiency as 1017. I can see this being a good option for the US.

Wow, that's pretty good.