Elevated errors on Claude Opus 5

6 hours ago (status.claude.com)

These bursts of downtime are one of the reasons I end up with multiple smaller subscriptions between providers.

I'd just end up being really annoyed about the downtime if it lands in the middle of a working day.

  • Not sure if it’s just me but in Codex, GPT-5.6-Sol and IIRC older 5.5 models can stop dead in the track a couple times a day saying “model is at capacity” (paraphrasing). Then I wait a minute or two and ask it to continue and it’ll more often than not happily use the same model. These frequent mini “outages” are pretty annoying especially if one isn’t supervising. Claude has had long outages but I haven’t run into this kind of mini outages on a daily basis recently.

    • Hermes seems to pick up after a stoppage. At least I've never had to push it again, it might just take a long time to finish a task and then I'll see the messages in the transcript.

Lots of errors. Opus 5 is also giving me many more hallucinations, including things that aren't even in the right territory. It's also telling me that it's making many mistakes, and the language feels off-kilter as if it's not using typical clear phrases.

  • Quality of output of both Fable and Opus seems to have gone down quite a bit over the past week. Many mistakes.

  • Yeah I noticed informing me of mistakes it made during sessions. It felt really off when it informed me of a mistake it almost made but caught it before it landed.

  • It is aggressively proactive in ways that make it very hard to use. I had to turn down the effort level to “low” to stop it from going off in random directions every couple of turns.

I would say "Elected errors _in_ Claude Opus 5" wouldn't be incorrect either.. Opus 5 isn't very reliable for coding and introduces a lot of regressions every single time I use it. Do you have the same experiences?

  • I also found it to forget some obvious cases in a quite simple flow (validate the email address of a user who register), that surprised me a lot. Maybe it's because I got used to Fable? But I am quite sure Opus 4.8 wouldn't have make this mistake. If I had time I would try the same prompt with it to see. Anyway, back on 100% Fable for me.

  • I don't know what I could be doing differently to you but I found Opus 5 to be more reliable than even myself at times. Maybe your stack is unusual or you have conflicting commands in your prompts vs CLAUDE.md (that really confuses it)? It could be anything but this huge error bar in delivered quality is one of the biggest issues with LLMs.

  • Getting to grips with each new model does require some tweaking and experimentation. So far I've found Opus 5 to repeatedly pause its work and give me some seemingly randomly invented decisions to make.

  • Opus 5 isn't very reliable for coding and introduces a lot of regressions every single time I use it.

    And GPT 5.6 Sol over engineers just about everything. No LLM is perfect, its about learning the issues with each LLM and figuring out if you can live with it. Knowledge means that you can anticipate if it tries to pull something funny, and harness it against that behavior.

    • this would be _Great_ advice if you owned your own LLM and your knowledge was trapped in Amber because you were satisfied.

      It's horrible advice given what we've seen consistent: changing alignments, changing guardrails, changing system prompts, changing inference priorities, etc.

      Anyone who relies on these for their work product is chaining themselves to a matrix multiple of indetermintism.

  • Same here, also it lies often to me or implements something else that what was planned. It feels quite strange to see it say casually "I didn't tell you the full truth on X" when I notice the issues. At the same time, maybe it is more honest?

  • Do you not have unit tests, or how does it introduce regressions? You can tell it how to run the test suite in CLAUDE.md

Operationally (and anecdotally obv) we've found that accessing Claude via AWS Bedrock has been notably more stable than direct to Anthropic.

  • We actually tracked this over the last year, bedrock is significantly better than the anthropic direct endpoints