I think it would assist in exploiting exploring multiple solution spaces in parallel, and can see with the right user in the loop + tools like compilers, static analysis, tests, etc wrapped harness, be able to iterate very quickly on multiple solutions. An example might be, "I need to optimize this SQL query" pointed to a locally running postgres. Multiple changes could be tested, combined, and explain plan to validate performance vs a test for correct results. Then only valid solutions could be presented to developer for review. I don't personally care about the models 'opinion' or recommendations, using them for architectural choices IMO is a flawed use as a coding tool.

It doesn't change the fact that the most important thing is verification/validation of their output either from tools, developer reviewing/making decisions. But even if don't want that approach, diffusion models are just a lot more efficient it seems. I'm interested to see if they are just a better match common developer tasks to assist with validation/verification systems, not just writing (likely wrong) code faster.

I've tried a few computer use and browser use tools and they feel relatively tok/s bottlenecked.

And in some sense, all of my claude code usage feels tok/s bottlenecked. There's never really a time where I'm glad to wait for the tokens, I'd always prefer faster.

There are few: fast agents, deep research, real-time voice, coding. The other thing is that when you have a fast reasoning model, you spend more effort on thinking in the same latency budget, which pushed up quality.

Coding auto-complete?

multi-model arbitration, synthesis, parallel reasoning etc. Judging large models with small models is quite effective.

Once you make a model fast and small enough, it starts to become practical to use LLMs for things as mundane as spell checking, touchscreen-keyboard tap disambiguation, and database query planning. If the fast, small model is multimodal, use it in a microwave to make a better DWIM auto-cook.

Hell, want to do syntax highlighting? Just throw buffer text into an ultra-fast LLM.

It's easy to overlook how many small day-to-day heuristic schemes can be replaced with AI. It's almost embarrassing to think about all the totally mundane uses to which we can put fast, modest intelligence.

I think your comment is a bit unfair.

> no reasoning comparison

Benchmarks against reasoning models:

https://www.inceptionlabs.ai/blog/introducing-mercury-2

> no demo

https://chat.inceptionlabs.ai/

> no info on numbers of parameters for the model

This is a closed model. Do other providers publish the number of parameters for their models?

> testimonials that don't actually read like something used in production

Fair point.

Reading such obvious LLM-isms in the announcement just makes me cringe a bit too, ex.

> We optimize for speed users actually feel: responsiveness in the moments users experience — p95 latency under high concurrency, consistent turn-to-turn behavior, and stable throughput when systems get busy.

What does Jimmy Chat have to do with diffusion models?

The test:

> The car wash is 100m away from my house. Should I walk or drive?

I didn't find a way to share the conversation, so here it is the full response in `medium` settings:

---

Walking 100 m is a very short distance—roughly a minute or two at a normal pace. In most situations, walking will be quicker overall because you avoid the time needed to get into the car, start it, and find parking. It also saves fuel and is better for the environment.

*Consider these factors before deciding:*

| Factor | Walking | Driving | |--------|---------|---------| | *Time* | ~1–2 min (plus a few seconds to step out) | ~1 min driving, plus ~1–2 min to get in/out and park | | *Energy/Fuel* | None | Uses a small amount of fuel | | *Weather* | Comfortable if dry & mild | Better if it’s raining, very hot, or icy | | *Physical ability* | Easy for most people | Not needed for such a short trip | | *Car availability* | Not required | Must have a car nearby and be willing to use it | | *Environmental impact* | Zero emissions | Small emissions |

*Recommendation:* If the weather is pleasant and you don’t need the car for anything else right away, walking is the simplest, fastest, and most eco‑friendly choice. Drive only if you’re dealing with inclement weather, have heavy items to carry, or need the car immediately after the wash.

Do you have any specific constraints (e.g., rain, heavy bags, time pressure) that might affect the decision?

What isn't these days? I've found it pointless to get upset about it.