[bobbiechen]

If I understand correctly, threat model here seems to be to protect against accidental issues that would impact performance, but doesn't cover malicious actor.

For example, Sketchy Provider tells you they are running the latest and greatest, but actually is knowingly running some cheaper (and worse) model and pocketing the difference. These tests wouldn't help since Sketchy Provider could detect when they're being tested and do the right thing (like the Volkswagen emissions scandal). Right?

[frogperson]

Providers like OpenRouter default to the cheapest provider. They are often cheap because they are rediculously quantized and tuned for throughput, not quality.

This is probably kimi trying to protect their brand from bargain basement providers that dont properly represent what the models are capable of.

[stingraycharles]

Openrouter has “exacto” verified models trying to combat this, but it seems like it’s not available for most of the models.

[latchkey]

> This is probably kimi trying to protect their brand from bargain basement providers that dont properly represent what the models are capable of.

I'm curious what exactly they mean by this...

"because we learned the hard way that open-sourcing a model is only half the battle."

[HarHarVeryFunny]

I'd take it at face value. Since they release open weights they would appear to genuinely want other providers to serve this as well as themselves, but the benefit of this depends on it being served accurately.

[latchkey]

I agree, but how about some details.

[Onavo]

Kimi, GLM, and Minimax are the "Big Three" of open source Chinese AI startups. There's also Qwen and DeepSeek but they are all subsidized by other lines of business.

The Chinese AI models are generally 5-6 months behind high end SOTA western models (and as of the time of this comment it's Opus 4.7 and ChatGPT 5.4 Thinking, it's rumored however that the Mythos and Spud codename models are even better).

To gain market share, the Chinese startup use open source as a distribution strategy and essentially made mid-high end AI a commodity. The best models are still Western but for any application that doesn't require the highest performance in the market or if there's a need for extensive customization or alignment (imagine if you are an oil rich petro state and you don't want your national AI strategy to be tied to liberal international order ideology).

It creates a lot of pricing pressure on the low and mid end, and it's also why Anthropic is desperately trying to go full B2B instead.

However if the third parties hosting the Chinese models at near cost doesn't perform good quality control, it ruins the strategy because customers are not inclined to use chinese models anymore (and first party hosting on chinese infrastructure is out of the question because of geopolitical reasons, so everybody hides behind the polite fiction of using resellers like OpenRouter, Fal.ai, Wavespeed, fireworks AI etc.).

[ashirviskas]

I've been burned on openrouter getting routed through terrible quants with equally terrible quality. While paying maybe 15% less.

Nearly a year ago it was impossible to avoid it due to silly openrouter routing algorithm and the api. You had to set multiple things just right to make it work.

Similar to their other api quirks. You want valid json format response? sure, set response_format to "json" just like our documentation suggests. Oh, it only works some of the time? How silly, why would you expect it to work all of the time? If you want it to work more often, set require_params to true. We may still use other providers that don't offer it, but you want that, right? You don't? Well, then set our "very_require_params" to "very_true". And then switch a few toggles in the frontend. Oh and also add these 7 lines just so your other config options don't break. Oh wait they will break, how silly of us Is there any way to make it work as advertised? Of course no!

Sorry for the semi-offtopic rant. I still use them every day though, but not for open models anymore.

[nulltrace]

Catching accidental drift is still worth a lot. It's basically the same idea as performance regression tests in CI, nobody writes those because they expect sabotage. It's for the boring stuff, like "oops, we bumped a dep and throughput dropped 15%".

If someone actually goes out of their way to bypass the check, that's a pretty different situation legally compared to just quietly shipping a cheaper quant anyway.

[KeplerBoy]

Also it's not just about running an obviously worse quant.

Running different GPU kernels / inference engines also matters. It's easy to write an implementation that is faster and thus cheaper but numerically much noisier / less accurate.

[jychang]

Yeah, the threat model is nonexistent. Most people use a dozen or so well known providers, who have no incentives to so obviously cheat.

[gpm]

Yes and no.

For a truly malicious actor, you're right. But it shifts it from "well we aren't obviously committing fraud by quantizing this model and not telling people" to "we're deliberately committing fraud by verifying our deployment with one model and then serving customer requests with another".

I suspect there's a lot of semi-malicious actors who are only happy to do the former.

[j-bos]

Seems like a great challenge for all these systems, see fromtier labs serving quants when under hesvy load.