I tried the cheapest provider on openrouter and burned through $50 in a few days. Quality was ok, seems slightly above Luna quality perhaps? But that $50 is 1/4 of my codex subscription where I could have burned that many tokens or more using Astra within my weekly reset.

This won’t last forever but as long as the frontier labs are subsidizing this heavily the open models won’t matter.

VRAM & Memory Requirements by Precision

• FP16 (Full Precision): Requires ~1,664 GB of VRAM (e.g., an 8x B300 288GB cluster).

• INT8 Quantization: Requires ~832 GB of VRAM (e.g., 8x H200 141GB).

• INT4 Quantization: Requires ~416 GB of VRAM (e.g., 8x A100 80GB)

VRAM aint cheap, Sam Altman ruined the cost of memory, Nvidia doesnt make enough consumer GPUs letting the market go insane over them, I still have friends on 1070s or 1070 TIs because GPUs have been severely overpriced for too long. I remember when a gaming PC was only $1000.

Even so why would anyone not sleep on a model they cannot run?

I don't think those subscriptions nave negative contribution margins, either. I think we're seeing a lot of price discrimination by the big labs, and huge margins on their frontier models. The fact that they have been cutting prices to their second-biggest tier of models (Opus/Sol).

Open models catching up and collapsing these margins would worry me if I were a shareholder in the big labs, but as a user, I really doubt that the western labs have bigger environmental impact just because they have higher API costs, I think they have a ton of efficiencies they aren't sharing with customers yet because demand is so high.

Once its gets juicier, we let flash launch specialized subagents with specific models. GLM-5.3 for coding or Kimi K.3 for research and critique.

But as a main driver. I love flash. And it brought our bill down by A LOT :D

I was previously using GLM-5.3 as the orchestrator, after switching to DS anecdotally there was an unnacceptable quality loss, mostly around not taking all the relevant context into account when making decisions, pulling new design out of thin air without discussion too often, and being way too wordy and rambly in documentation despite prompting to avoid it. There's a lot of docs, rulings, core concepts, design philosophy to uphold and DS was just not cutting it.

However, it's perfectly capable of being the sole agent for all of my well specced implementation tasks. I've gone back to GLM as the orchestrator.

These open models still did not beat February's Mythos / Fable 5.

DeepSeek 4.1 Flash is behind GPT 5.6 Sol, and that one is left in the dust by the excellent Opus 5.5.

Rumors say Anthropic is holding in reserve the big improvement, Fable 5.5, for the IPO.

It's plausible that open models are 6 - 12 months behind, and there is no "good enough". As long as progress doesn't slow down, leading labs have nothing to fear.

Unfortunately, it looks like Cursor doesn't support DeepSeek... but I can say that for lots of tasks, the cheapest models do just fine, too. Of course there are cases where they just keep spinning for 30 minutes without being able to figure things out, but in those cases, I just retry on a slightly more expensive, hopefully better model.

Some of the models are so good and cheap, not sure about the frontier labs and their multi-trillion dollar evaluation. Sometimes "good enough" is really good enough.

I am a big ChatGPT fan, all our team has ChatGPT Subs, but the TPS across all models including luna is just so damn slow.

Commandcode giving 60$ worth of Deepseek for 10$ is just genuinely goat.

And it never says no for cyber tasks so that's a big win

My OpenCode Go monthly window was scheduled to reset this morning. It was sitting at 22% used despite me using DeepSeek V4.1 Flash heavily as my implementation agent the past couple weeks (I use gpt-6.1-sol high for planning/orchestration).

I had 1.5 hours left so I fired up first 10, then 20, and finally 50 concurrent subagents all working on reverse engineering C code from an old PC game. They found over 100 new functions.

This is the first workload I've found that could make a dent in my sub. It got my 5 hour window to 85% used, but sadly my monthly was still only at about 35% when it reset. So that cost maybe $2.

The other reason is more interesting. Maybe the frontier providers think that price performance is irrelevant in light of very powerful frontier models that can start the RSI loop and or a huge displacement of work and a winner take all economic situation. After all if frontier providers earn everyone's money then you won't have any money to spend on any model 100x cheaper or not.

I realized that mistake and guided DeepSeek where it should be.

Next I fired Fabble 5.5 set to high to check if the hype is real about Fabble. It exhausted 89% of quota and came up with NOTHING that DeepSeek hadn't flagged itself already in its notes.

That said, it's my best understanding that these american companies aren't profitable and will eventually raise rates (the old uber trick) so I'm keeping myself ready to switch when that day comes.

I’m convinced that I’ll have good enough inference on my laptop at reasonable speeds within the next year.

see https://artificialanalysis.ai/models/releases/comparisons?co...

And yes, Opus is enough smarter than DSF that it's worth the extra steps. This ranking is from live tickets, no contamination: https://slopcop.com/power-ranking

Is OpenAI coming in $20B under a sign of "freaking out"?

(And what are the preferred providers?)

are you worried about sending all your data to third parties, especially if they're in different countries?

Anthropic and OpenAi are in the news, so they get the press and people go and try out their product. Large enterprise businesses are going to make larger, longer-term contracts with them and are only going to pivot if they think switching costs are easy or if they think the provider won't deliver.

The other inference producers are less well known or you need to get your cloud sales rep to tell you how to switch to them as a provider rather than Anthropic or OpenAI.

I use OpenRouter, I know switching is easy, but larger businesses tend to work in yearly cycles. DeepSeek v4 Flash came out in late April.

I agree OpenAI and Anthropic are going to struggle when the median price of running a smart-enough model keeps falling.

Edit: I also think demand for hardware will be rapidly absorbed by other companies if Anthropic or OpenAI stumble. We've finally turned hardware directly into runnable intelligence and people are not going to go back to the old ways.

People tend to conflate the question "is AI a useful technology?" with "are the AI companies going to do well?" but they're surprisingly separated in practice, with either one able to be true while the other is false. There is a lot of money tied up in a lot of hardware with a lot of loans made against that hardware as collateral all based on the assumption that AIs are going to need more and more and more and more hardware and whoever has the hardware wins. If a much better model comes out that requires vastly less hardware, or even more accurately, merely charges vastly less than the current AI companies, then to a first approximation (barring Jevon's paradox, and bearing in mind there's no timeline guarantee on that) all that hardware becomes much less valuable for being grotesquely oversupplied relative to what is necessary, and even though that would generally make AI objectively more useful than it was before, it would cause mass financial chaos in the markets.

The markets need a very particular rate of progress. It isn't entirely clear to me that it's even a possible rate of progress, it may be overconstrained, but they certainly don't have plans for the AI models to get commoditized on the timeframes of these vast, vast array of loans being made against hardware as collateral. Spend a metric shit ton of money to kill all your competition then charge monopoly rent on the one thing absolutely everyone needs doesn't work if you can't economically "kill all your competition" because the economics favor them in the spending spree.

And then, based on the fact that this is not even remotely complicated logic, there are plenty of people who are fully aware that they have a lot of money tied up in not running around telling everyone how wonderful the cheap models have become.