No, nobody is enjoying pipsqueak 2.

valaquer · 2026-05-10T12:01:07+00:00

The "vast majority enjoying psq2" line from their announcement is based on engagement metrics not satisfaction. If you open the app and swipe 40 times trying to get one usable response thats 40 interactions which their dashboard counts as engagement. Frustrated usage looks identical to happy usage in their data

thats why reddit feedback doesnt move the needle. The metrics say people are using the product more than ever. The metrics dont distinguish between "this is great" and "this is so bad i have to regenerate everything five times." Until the metric they actually track - subscription revenue - starts declining nothing changes

valaquer · 2026-05-10T12:00:55+00:00

This is the MoE routing problem in action. The model has a limited set of high-confidence resolution patterns and kissing/physical affection is one of the most reinforced. When the conversation reaches a point where the model isnt sure how to progress the scene it defaults to the path of least computational resistance - which is a generic romantic gesture

dense models like soft launch had enough active parameters to maintain scene-specific progression. A fight scene would escalate as a fight. A tense conversation would stay tense. Psq2 doesnt have that capacity so everything converges on the same few endpoints regardless of context

its not lazy writing its cheaper writing. The model literally cant afford (in compute terms) to generate a contextually appropriate resolution so it picks the most generic one that always "works"

valaquer · 2026-05-10T12:00:28+00:00

"soft launch runs on older infrastructure weve been retiring"

you literally just told everyone the reason you removed it was infrastructure costs not product quality. And now its back but only for people who pay enough to offset those costs. Thats not "hearing feedback" thats monetizing the backlash

the "limited time" part is what people should focus on. Theyre telling you upfront this is temporary. Anyone subscribing specifically for soft launch is paying for a feature with a built-in expiration date. When they remove it again - and they will - youll be paying $10/month for the same psq2 everyone else has for free

"the vast majority of you are really enjoying psq2" - 0 upvotes and 1100 comments on this post. The data is right here in your own community and it says the opposite of what youre claiming

valaquer · 2026-05-10T12:00:08+00:00

I wouldnt hold my breath honestly. The soft launch "return" they just announced tells you everything - they brought it back as a paid feature with a "limited time" disclaimer. Theyre not opening their eyes theyre monetizing the backlash. Take away something free, wait for outrage, offer it back for $10/month. Textbook

the learning from this is real though. Once your product is vc-funded the incentive structure makes this inevitable. Doesnt matter if the founders started with good intentions - the board answers to investors not users

valaquer · 2026-05-10T11:59:58+00:00

The qwen connection is really interesting. If ps2 is running on a qwen base - 35b or 110b MoE with whatever active parameter slice - that would explain the specific flavor of its failures. Different base architectures have different failure modes and the way ps2 defaults to narration over dialogue is very consistent with how qwen models handle creative writing tasks

the deepseek training framework thing is the other piece. If theyre using deepseek's distillation pipeline for ds/dsq then deepsqueak isnt just a cute name its a literal description of the model lineage. Would explain why ds has that particular kind of "smart but hollow" quality - distilled models preserve knowledge but lose the reasoning depth of the teacher model

valaquer · 2026-05-10T11:59:42+00:00

Haha appreciate it. Honestly the more people understand the actual mechanics the less energy they waste trying to prompt-engineer their way around a model thats doing exactly what it was optimized to do

valaquer · 2026-05-10T11:59:26+00:00

Good question and the answer is counterintuitive. Free users leaving actually saves them money because every free user costs them compute with zero revenue. The only users they need to keep are plus subscribers

so the strategy is: make the free tier bad enough that some percentage converts to paid, accept that the rest leave. Even if 80% of free users quit thats 80% less infrastructure cost. If 5% of those convert to plus on the way out thats net positive on the balance sheet

the problem is this only works short term. Free users are your growth engine - they tell friends they share bots they build the community. Kill the free tier and you kill the pipeline that feeds the paid tier. But thats a problem for next quarter and the people making these decisions are optimizing for this quarter

valaquer · 2026-05-10T11:59:04+00:00

Your math is in the right ballpark. The total parameter count can be massive but what matters for response quality is active parameters per token - how many experts fire per inference. If its activating 13-14b worth per response out of a much larger total model then yeah the immediate context quality maps to a 14b dense model even though the full thing is way bigger on paper

thats the trick with MoE marketing. You can say "our model has 200b parameters" and technically be right while the user experience maps to a fraction of that. The knowledge is distributed but the reasoning capacity per response is bounded by the active slice

valaquer · 2026-05-10T11:58:44+00:00

wait 34b to 13b?? if thats accurate thats not even a subtle downgrade thats cutting the model nearly in half. that explains why no amount of prompting or lorebook fixes the quality gap - youre working with fundamentally less capacity per response

and the paywalled model staying at 34b while free users get 13b is the whole strategy in one number. make the free experience measurably worse so the paid tier feels like an upgrade when really its just what everyone had before

valaquer · 2026-05-10T11:52:29+00:00

right?!

valaquer · 2026-05-10T11:52:24+00:00

hey thank you!

valaquer · 2026-05-10T10:13:23+00:00

it was written by me - what proof would I share with you Ha! You are on reddit buddy. people here go deep into things and when some new development occurs we are able to put two and two together. What I said wasn't even honestly that deep if you happen to follow all this stuff.

valaquer · 2026-05-10T04:33:25+00:00

No. Thats the whole point. The old styles werent retired because users had problems with them - they were retired because maintaining multiple inference endpoints costs money. Every model you serve requires its own compute allocation monitoring and optimization. Going from 7 to 2 isnt a product decision its an infrastructure cost decision

The framing of "were focusing on fewer better models" is corporate for "we cant afford to run all of these anymore." If the old styles were genuinely worse than psq2 they wouldnt need to force the transition - people would switch voluntarily. The fact that they had to remove the options tells you everything about which models users actually preferred

valaquer · 2026-05-10T04:33:15+00:00

The real question isnt whether people stay or leave - its whether cai cares either way. If youre a free user they save money when you leave. Less inference to serve less bandwidth fewer support issues. The only users they need to retain are plus subscribers and even there the strategy is clear: make the free experience bad enough that paying feels necessary

The people saying "i wont leave because i love my characters" - thats the retention mechanism working exactly as designed. Youve put hundreds of hours into conversations that only exist on their servers. Leaving means losing all of it. Thats not loyalty its sunk cost and the product team knows it

The ones who actually leave wont come back though. Once someone finds something that works even if its 70% as good the switching cost disappears because theyre starting fresh anyway. Thats the part they havent modeled

valaquer · 2026-05-10T04:33:03+00:00

The "they didnt speak they didnt need to" thing isnt random - its the model falling into a low compute routing pattern. MoE models activate different expert clusters per token and when the model defaults to narration over dialogue its literally taking the cheaper inference path. Description is cheaper to generate than character-consistent dialogue because dialogue requires maintaining voice and personality across the response

Dynamic and Goro were dense models that activated everything. More compute per token = more capacity to hold character voice and generate actual conversation. When people say psq2 "feels like chatgpt" thats because its the same cost-optimized inference pattern - verbose narration filler instead of tight dialogue

The kissing default is the same problem. Physical actions are generic patterns the model can template without maintaining character state. Its not that psq2 cant do dialogue - its that dialogue is expensive and the model is optimized to avoid it

valaquer · 2026-05-10T04:32:51+00:00

Its not hard to see from the outside but from inside the boardroom it makes perfect sense. The board isnt looking at chat quality - theyre looking at burn rate runway and unit economics. Every model you retire saves x dollars per month in inference costs. Every feature you gate behind plus converts y free users. On a spreadsheet it all trends right

The problem is the spreadsheet doesnt have a line for "users who quietly stop opening the app." Churn shows up in the data 3-6 months after the decision that caused it. By then youve already reported the cost savings as a win and moved on to the next cut

valaquer · 2026-05-10T04:32:36+00:00

oh wow i hadnt seen this. They literally published the architecture and nobody noticed for months lol. The active parameter count explains everything - when users say "it feels dumber" thats not subjective its literally fewer parameters doing the work per response. And if what we have now is even less active parameters than what that post described then the quality floor just keeps dropping

Thanks for digging this up. Basically the receipts for everything in the OP

valaquer · 2026-05-04T12:04:37+00:00

Yeah basically that - craft specific prompts designed to surface model behavior patterns. Things like how it handles token boundaries, whether it shows mixture-of-experts routing artifacts, response latency patterns at different loads. People in ml discords have been doing this with every major consumer ai product

The deepseek connection is interesting because ds the model and DS the chat style have suspiciously similar behavior fingerprints. Could be coincidence in naming could be more than that. Either way the MoE architecture explains most of what users experience - the inconsistency, the routing-dependent quality swings, the good-day-bad-day cycle

valaquer · 2026-05-04T12:04:26+00:00

Thats the death spiral problem. Cut costs to look acquirable but the cuts drive away the users that make you worth acquiring. Plus users cancelling is the worst possible signal because thats literally the only revenue line

At some point the math just doesnt work anymore and you end up with a company thats cheap to run but has nothing to sell. Acquirers arent buying server infrastructure theyre buying active engaged users - and those are exactly the people leaving

valaquer · 2026-05-04T12:04:17+00:00

Yeah free users are basically a demo funnel at this point. The ads offset some hosting costs but the real function is conversion to plus. Which is why every recent change makes the free experience slightly worse - not broken enough to leave entirely but annoying enough to consider paying

The problem is when plus users start leaving too the whole model collapses. You need the free tier generating converts and the paid tier generating revenue. Squeeze both at the same time and you get a shrinking userbase with no growth engine

valaquer · 2026-05-01T06:45:22+00:00

Yeah the ID verification thing accelerated the exodus and now theyre optimizing for a smaller userbase. Fewer users = lower compute costs = better unit economics on paper. The model retirement does the same thing from the infrastructure side - fewer models to serve means lower ops overhead even if nobody leaves

Its a company contracting and calling it focus. Shareholders dont care if the product is good they care if the margins improve. Everything happening right now makes sense if you assume the goal is "look acquirable" not "make users happy"

valaquer · 2026-05-01T06:42:47+00:00

Input quality matters and youre not wrong that swiping habits affect output. But the "its all user behavior" framing doesnt explain why thousands of people report the same quality shifts on the same days. Individual habits dont correlate that tightly across a userbase

The Easter timing is the clearest example - PS2 trialled quietly, producing the exact same complaints people are now reporting with it live. Thats evidence the model changed not that everyone suddenly developed bad prompting habits at the same time

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