Do they credit your account if you were impacted? Or it's just "sorry 'bout 'dat month of trash"?
Unfortunate timing, as I am rooting for Anthropic as the underdog, but feel compelled to use whatever works best. Since mid-August I've demoted Claude to only putting the fire on UIs and am getting amazing results with GPT-5 for everything else. Given the nonstop capacity warnings on codex cli, I might not be the only one.
> Unfortunate timing, as I am rooting for Anthropic as the underdog...
Give me a break... Anthropic has never been the underdog. Their CEO is one of the most hypocrite people in the field. In the name of "safety" and "ethics", they got away with not releasing even a single open-weight (or open-source) model, calling out OpenAI as the "bad guys", and constantly trying to sabotage pro-competition and pro-consumer AI laws in the US.
My guess would be that they tried to save money with speculative decoding and they had too loose thresholds for the verification stage.
As someone who has implemented this myself, I know that it’s pretty easy to make innocent mistakes there. And the only visible result is a tiny distortion of the output distribution which only really becomes visible after analysing thousands of tokens. And I would assume that all providers are using speculative decoding by now because it’s the only way to have good inference speed at scale.
As a quick recap, you train a small model to quickly predict the easy tokens, like filler words, so that you can jump over them in the recurrent decoding loop. That way, a serial model can predict multiple tokens per invocation, thereby easily doubling throughput.
And the fact that they need lots of user tokens to verify that it works correctly would nicely explain why it took them a while to find and fix the issue.
Would that show up more with heavily cached data or less? Because I've been using very heavily cached data on the order of 30 to 1 cache versus not. And I haven't had much trouble with Claude Code at all in the last month. A few problems here and there, but they were sporadic. While I know other people have had massive issues, I wonder if the issues that occurred didn't effect cache as much and thus prevented me from seeing some of the worst aspects of it.
Standard speculative decoding without relaxed acceptance has no accuracy impact as far as I understand things. If you always run the verification; you always have the true target model output.
They already have a track record of messing with internal system prompts (including those that affect the API) which obviously directly change outputs given the same prompts. So in effect, they've already been messing with the models for a long time. It's well known among founders who run services based on their products that this happened, everyone who does long output saw the same. It happened around November last year. If you had a set of evals running that expected an output of e.g. 6k tokens in length on 3.5 Sonnet, overnight it suddenly started cutting off at <2k, ending the message with something like "(Would you like me to continue?)". This is on raw API calls.
Never seen or heard of (from people running services at scale, not just rumours) this kind of API behaviour change for a the same model from OpenAI and Google. Gemini 2.5 Pro did materially change at time of prod release despite them claiming they had simply "promoted the final preview endpoint to GA", but in that case you can give them the benefit of it being technically a new endpoint. Still lying, but less severe.
Anthropic have frequently claimed that they do not change the model weights without bumping the version number.
I think that is compatible with making "changes intended to improve the efficiency and throughput of our models" - i.e. optimizing their inference stack, but only if they do so in a way that doesn't affect model output quality.
Clearly they've not managed to do that recently, but they are at least treating these problems as bugs and rolling out fixes for them.
And I think it was 100% on purpose that they degraded the model performance as Claude Code got so popular and they either ran out of capacity or were losing money too fast.
But now that people are fleeing to Codex as it improved so much during the time, they had to act now.
I wonder how long the myth of AI firms losing money on inference will persist. Feels like the majority of the evidence points to good margins on that side
So they aren’t saying what the bug was that caused this issue? Would love a more detailed explanation, what could possibly cause the model degradation apart from potentially pointing the queries to the wrong model?
This is why it is hard to take a subscription or dependency on them, if they degrade the services willy nilly. Bait and switch tactic.
In Cursor I am seeing varying degrees of delays after exhausting my points, for On-Demand Usage. Some days it works well, other days it just inserts a 30s wait on each message. What am I paying for? You never know when you buy.
You should never buy annual AI subs. This field moves so fast and companies often change their ToS. Poe.com did the same and I was out (one day they decided to change the quotas/month for the SOTA models and turned off the good old GPT-4 and replaced it with GPT-4-Turbo which was quantized and bad).
The model providers should analyse the tone of the instructions.
Before I finally gave up on Claude Code, I noticed that I got more aggressive towards it, the more stupid it got as I could not believe how dumb it started to be.
Anthropic can't seem to get a win lately. Claude code hangover, their lunch is getting eaten by Chinese OSS on the value side and GPT-5 High on the quality side.
I may be in a minority but I am still quite bullish on them as a company. Even with GPT-5 out they still seem to have a monopoly on taste - Claude is easily the most "human" of the frontier models. Despite lagging in features compared to ChatGPT Web, I mostly ask Claude day-to-day kinds of questions. It's good at inferring my intent and feels more like a real conversation partner. Very interested to see their next release.
My biggest concern now is — if the issue they have is as vague as “reports of degraded quality”, how do they even approach fixing it? And what measurable criteria will they use, to declare that it is fixed? Would they take a vibes-check opinion poll?
Curious why they can’t run some benchmarks with the model (if they suspect the issue is with the model itself) or some agentic coding benchmarks on Claude-code (if the issue might be with the scaffolding, prompts etc).
Here’s a report: Claude Code (the software) is getting worse by the day.
Removing the shown token comsumption rates (which allowed understanding when tokens were actually being sent / received!) … sometimes hiding the compaction percentage … the incredible lag on ESC interruption on long running sessions, the now broken clearing of the context window content on TASK tool usage
Who the fuck is working on this software and do they actually use it themselves?
Maybe the quality of Claude Code on any given day is indicative of whether their models are degraded …
Claude Code is indeed legit bad. You'd never know that this was a billion dollar company by the mess of javascript they hacked together. You have to periodically close and re-open the client because otherwise it starts to lag the system from constantly scanning and saving a big JSON file, and they didn't think to shard their storage or use a database. I have 128GB of ram on my workstation and running 8 claude code instances at once sometimes causes heavy thrashing and desktop responsiveness issues... That's just insane.
Needless to say I built my own agent (just needs a good web UI, last step!). The only thing keeping me with anthropic right now is the economics of the plan, my inference bill would be a second mortgage without it.
That's a weird summary given how many people around me use Claude with Cursor and still prefer it over gpt5. I don't think you can claim a complete view of what their customers want.
>Importantly, we never intentionally degrade model quality as a result of demand or other factors, and the issues mentioned above stem from unrelated bugs.
Sure. I give it a few hours until the prolific promoters start to parrot this apologia.
Don't forget: the black box nature of these hosted services means there's no way to audit for changes to quantization and model re-routing, nor any way to tell what you're actually getting during these "demand" periods.
metadat|5 months ago
Unfortunate timing, as I am rooting for Anthropic as the underdog, but feel compelled to use whatever works best. Since mid-August I've demoted Claude to only putting the fire on UIs and am getting amazing results with GPT-5 for everything else. Given the nonstop capacity warnings on codex cli, I might not be the only one.
behnamoh|5 months ago
Give me a break... Anthropic has never been the underdog. Their CEO is one of the most hypocrite people in the field. In the name of "safety" and "ethics", they got away with not releasing even a single open-weight (or open-source) model, calling out OpenAI as the "bad guys", and constantly trying to sabotage pro-competition and pro-consumer AI laws in the US.
dinfinity|5 months ago
paulddraper|5 months ago
fxtentacle|5 months ago
As someone who has implemented this myself, I know that it’s pretty easy to make innocent mistakes there. And the only visible result is a tiny distortion of the output distribution which only really becomes visible after analysing thousands of tokens. And I would assume that all providers are using speculative decoding by now because it’s the only way to have good inference speed at scale.
As a quick recap, you train a small model to quickly predict the easy tokens, like filler words, so that you can jump over them in the recurrent decoding loop. That way, a serial model can predict multiple tokens per invocation, thereby easily doubling throughput.
And the fact that they need lots of user tokens to verify that it works correctly would nicely explain why it took them a while to find and fix the issue.
metadat|5 months ago
mickdarling|5 months ago
buildbot|5 months ago
irthomasthomas|5 months ago
I thought Anthropic said they never mess with their models like this? Now they do it often?
jjani|5 months ago
Never seen or heard of (from people running services at scale, not just rumours) this kind of API behaviour change for a the same model from OpenAI and Google. Gemini 2.5 Pro did materially change at time of prod release despite them claiming they had simply "promoted the final preview endpoint to GA", but in that case you can give them the benefit of it being technically a new endpoint. Still lying, but less severe.
simonw|5 months ago
I think that is compatible with making "changes intended to improve the efficiency and throughput of our models" - i.e. optimizing their inference stack, but only if they do so in a way that doesn't affect model output quality.
Clearly they've not managed to do that recently, but they are at least treating these problems as bugs and rolling out fixes for them.
mccoyb|5 months ago
naiv|5 months ago
And I think it was 100% on purpose that they degraded the model performance as Claude Code got so popular and they either ran out of capacity or were losing money too fast.
But now that people are fleeing to Codex as it improved so much during the time, they had to act now.
deepdarkforest|5 months ago
theshrike79|5 months ago
But alas it's not. It looks like some intern whipped it together.
rsanek|5 months ago
unknown|5 months ago
[deleted]
andy_ppp|5 months ago
qsort|5 months ago
visarga|5 months ago
In Cursor I am seeing varying degrees of delays after exhausting my points, for On-Demand Usage. Some days it works well, other days it just inserts a 30s wait on each message. What am I paying for? You never know when you buy.
behnamoh|5 months ago
naiv|5 months ago
Before I finally gave up on Claude Code, I noticed that I got more aggressive towards it, the more stupid it got as I could not believe how dumb it started to be.
And I am sure I was not the only one.
simianwords|5 months ago
And this bad memory might stick for a while.
BhavdeepSethi|5 months ago
extr|5 months ago
I may be in a minority but I am still quite bullish on them as a company. Even with GPT-5 out they still seem to have a monopoly on taste - Claude is easily the most "human" of the frontier models. Despite lagging in features compared to ChatGPT Web, I mostly ask Claude day-to-day kinds of questions. It's good at inferring my intent and feels more like a real conversation partner. Very interested to see their next release.
d4rkp4ttern|5 months ago
Curious why they can’t run some benchmarks with the model (if they suspect the issue is with the model itself) or some agentic coding benchmarks on Claude-code (if the issue might be with the scaffolding, prompts etc).
mccoyb|5 months ago
Removing the shown token comsumption rates (which allowed understanding when tokens were actually being sent / received!) … sometimes hiding the compaction percentage … the incredible lag on ESC interruption on long running sessions, the now broken clearing of the context window content on TASK tool usage
Who the fuck is working on this software and do they actually use it themselves?
Maybe the quality of Claude Code on any given day is indicative of whether their models are degraded …
yurifury|5 months ago
CuriouslyC|5 months ago
Needless to say I built my own agent (just needs a good web UI, last step!). The only thing keeping me with anthropic right now is the economics of the plan, my inference bill would be a second mortgage without it.
avishai2112|5 months ago
paradite|5 months ago
https://x.com/claudeai/status/1965208247302029728
viraptor|5 months ago
ziml77|5 months ago
behnamoh|5 months ago
- shitty voice to text (why not just use Whisper at this point?)
- clunky website
- no image/video generation models
- DeepResearch sucks big time
- "Extended Thinking" doesn't seem to do much "thinking". I get the same results without it.
- API too expensive for what it is.
- No open-weight model to boost their reputation. Literally every other player has released an open model at this point..
viraptor|5 months ago
troupo|5 months ago
stpedgwdgfhgdd|5 months ago
I want to know how i could have been impacted.
ares623|5 months ago
allisdust|5 months ago
Aeolun|5 months ago
Oh, let me just fix that!
Comments out test
slacktivism123|5 months ago
Sure. I give it a few hours until the prolific promoters start to parrot this apologia.
Don't forget: the black box nature of these hosted services means there's no way to audit for changes to quantization and model re-routing, nor any way to tell what you're actually getting during these "demand" periods.