re-thc

Anthropic levels of slowness (pacing)?

> Sol 6.1 scores one point less than Gemini 4 on intelligence AND costs less than half ($0.72 vs $1.99) per task.

Via the API. The $200 OpenAI plan just got cut and most say general quotas got cut before that so for users on a plan the numbers might be different.

That's a Fable / Myth(o). The name said so.

> I don't think cache read is a big portion of the overall cost.

For long running tasks it is. That's what made Deepseek so cheap.

IPO soon

You bet there will be a new Fable soon.

There were comparisons and Muse Spark is so very similar to Fable / Opus... so...

> You refuse a direct order.

I never said. It's not about outright refuse. It's how to deliver better outcomes. It's not a win or lose situation. Don't treat it like that.

> If your boss says that he does not care about long term consequences and he want things done a certain way

As suggested in my previous comment it could be you didn't explain it well. If you say code quality they might not care. Say it will crash randomly and can't fix it then they might. There's some art to it.

> Your opinion on what you think he wants is legally irrelevant.

No it's not. So you're saying if you got told to do something illegal you'd also do it anyway? I doubt it. You need to at least cover your back and document it as such. I'd say termination is better than jail.

> Where LLMs excel is in code-level bugs (as opposed to system bugs, design bugs, architecture bugs, integration bugs, etc).

Blame the benchmarks game. They're optimizing for that and that's what those things are measuring.

> Work for business people who want fast results. Agentic coding gets you to something presentable much faster at the cost of code quality. I have never seen a customer or business person care about that.

That's always false. It's like people want their meals delivered fast. They say they don't care about taste or how it is done. Watch when they get sick or don't like it and the drama that happens.

People don't care until they do. They don't know what to care (in this case code quality) or say that because you're not explaining it. People also "gamble" and you take the blame. Long term impacts? Nah doesn't matter. Weeks later and things break -- what did you do?

> A high score on benchmarks is not as useful because a model overtrained to always answer will give confidently wrong responses.

It's not useful because the benchmarks often measure the wrong thing. They're here yapping about AGI and yet the benchmarks treat it like a trained dog. Fetch this. 100 points.

Each "problem" in these benchmarks likely has more than 1 solution that can be considered correct and even should be graded in many ways. Yet we see in many benchmarks higher effort (or thinking levels) don't help because the benchmark penalizes for doing "more" than what the answers asks for. So what did you ask for?

In human school you often get marks on the process and not just the end result. Thinking tokens have been cut. All we group on is things like cost, turns and time but not the what else.

It did used to use Haiku but that model is now too too far behind…

Hardware definitely has longer lifecycle than AI model releases at this point.

You don't see Nvidia and AMD fighting every other month over the latest cards.

Overtaken in cost per token.

> DeepSWE is a very big deal

It's clearly been "dealt with" already. When it launched we had interesting gaps and definitely differences. Now every new release is "crushing it".