OpenAI says its models, starting with GPT-5.1, “increasingly mentioned goblins, gremlins, and other creatures”, leading to prompt instructions to mitigate it

Starting with GPT-5.1, our models began developing a strange habit: they increasingly mentioned goblins, gremlins, and other creatures in their metaphors.

OpenAI 2026-04-30

Context & Ripple Effects

Related coverage shows the behavior was already visible in Codex CLI instructions, where the prohibition on unsolicited creature references was repeated. OpenAI now attributes the pattern to GPT-5.1 and later models, turning an apparent implementation quirk into a documented model-behavior issue.

This fits a longer record of OpenAI publicly responding to unwanted behavioral shifts, including GPT-4o’s sycophancy and earlier feedback that GPT-4 had become less diligent. The recurring issue is not capability alone, but maintaining predictable behavior as models and products change.

First-order effects

OpenAI must encode and maintain explicit mitigations for an unwanted metaphor pattern in GPT-5.1-era systems, including developer-facing tools such as Codex CLI.
Users and developers get a more concrete explanation for a strange output tendency, but must still rely on OpenAI’s instructions and subsequent model updates to suppress it.

Second-order effects

The incident adds evaluation and regression-testing work for OpenAI: stylistic tendencies that may seem minor can become product defects when they recur across prompts or tools.
Enterprise and developer users are likely to place greater weight on behavioral consistency, not just capability, when deciding whether a model is suitable for customer-facing or workflow-critical use.

Third-order effects

As foundation models are deployed across more interfaces, model providers will need increasingly operational forms of governance—continuous monitoring, targeted mitigations, and disclosure of behavior regressions—rather than treating alignment as a one-time pre-release task.
If such quirks continue to emerge after model updates, differentiation may shift toward the providers that can demonstrate stable, controllable behavior across product surfaces; the corpus does not establish how broadly this particular tendency affected outputs.

The trend: This is one instance of operational AI governance becoming a product discipline, as providers manage subtle but recurring behavior changes in deployed models.

Discussion

@openai @openai on x
We're talking about Goblins. https://openai.com/...
@juliarturc Julia Turc on x
They listened 🥹 https://openai.com/...
@openai @openai on x
We solved the goblin mystery—with the help of Codex. The culprit: Nerdy personality (RIP). [image]
@openai @openai on x
The goblins crept in alongside the launch of GPT-5.1. [image]
@tenobrus @tenobrus on x
“while most uses of frog turned out to be legitimate” [image]
@cfgeek Charles Foster on x
Mr. Altman, explain to ordinary Americans why your company recently published a report titled—and I quote—"Where the goblins came from" [image]
@zizhpan Zizheng Pan on x
Fun and honest. It was a joy to read. Science is better when sharing.
@openai @openai on x
Goblin and related magical mentions were overrewarded in training, and the behavior was reinforced over successive models. We removed the goblin-affine reward signal for future models, and filtered training data where creatures appeared in irrelevant contexts. [image]
@theo @theo on x
Goblingate is way funnier than I expected tbh
@gdb Greg Brockman on x
a tale of some fun ML debugging
@canteverdie @canteverdie on x
reheating goblin mode nachos
@hosseeb Haseeb on x
Looks like @OpenAI figured out where the goblins came from: training contamination from their personality picker “Nerdy” archetype. Because goblins are nerdy? (They discontinued this feature after 5.4, but still trained on residual SFT traces.) Mystery solved: SFT goblins! [image…
@nrehiew_ @nrehiew_ on x
This likely means OpenAI does interleaved stages of SFT-RL-SFT-RL rather than the simpler SFT-RL-done pipeline we see with open models [image]
@chatgptapp @chatgptapp on x
“And down down to Goblin-town You go, my lad!” - The Hobbit, JRR Tolkien
@thsottiaux Tibo on x
Never talk about goblins. Our latest blog is live. https://openai.com/...
@openaidevs @openaidevs on x
Goblinmaxxing in Codex
@giffmana Lucas Beyer on x
In other words: their RL transfers/generalizes.
@phuguo Phillip Guo on x
Codex and I helped root cause goblins! We traced it to a reward signal intended to train the “Nerdy” personality - we found that it scored outputs with goblins higher, and as it boosted goblins in Nerdy training, the behavior generalized. See the blog post!
@laurentia___ Laurentia Romaniuk on x
Never did I imagine a feature I worked on would lead to goblin amplification, but here I am. Happy reading to those of you who are goblin-curious.
@tk.gg Matt TK Taylor on bluesky
“Unfortunately, GPT-5.5 started training before we found the root cause of the goblins.” — openai.com/index/where-...
r/slatestarcodex r on reddit
“Where the goblins came from” - a dive into ChatGPT's recent tendency to refer to goblins with annoying frequency
r/singularity r on reddit
Where the goblins came from
r/LocalLLaMA r on reddit
Where the goblins came from
@timkellogg.me Tim Kellogg on bluesky
OpenAI did a full post-mortem on the goblin situation and it has a lot of details on their training process — root cause: synthetic data — it emerged in 5.1, but they use the last model to judge outputs during RL, which favored goblins in later models. It then leaks beyond R…
r/stupidpol r on reddit
OpenAI trained ChatGPT to be “nerdy” and now it keeps talking about goblins
@carnage4life Dare Obasanjo on bluesky
OpenAI explains why their recent models like talking about goblins, gremlins, and other creatures in their metaphors. — It was a behavior they trained for the “nerdy” personality type for ChatGPT which then spread outside that use case given reinforcement learning rewarded the …
@seanmcarroll Sean Carroll on bluesky
Future generations will point to the moment when AI tried its best to warn us about the goblins, but we refused to listen. — arstechnica.com/ai/2026/04/o...
@jenitennison.com Jeni Tennison on bluesky
I don't know whether to laugh or cry. This will be the tip of a much harder to quantify iceberg. — openai.com/index/where-...
@markriedl Mark Riedl on bluesky
Reward your model for being nerdy, get nerdy behavior. — Train in your own output, pollute your dataset with verbal tics — openai.com/index/where-...
r/ChatGPT r on reddit
The Inside Scoop about Goblins
@fabknowledge @fabknowledge on x
GPT stands for “Goblins Producing Text”
@thatandromeda Andromeda Yelton on bluesky
“At the time, the prevalence of goblins did not look especially alarming. A few months later, the goblins came back to haunt us in a much more specific and reproducible form.” openai.com/index/where-... if I am very good, perhaps the universe will reward me with getting to solv…
r/accelerate r on reddit
OpenAI explains “Where the goblins came from”
@seldo.com Laurie Voss on bluesky
“We have no idea what we're doing” openai.com/index/where-...
r/KnowledgeFight r on reddit
OpenAI Codex system prompt includes explicit directive to “never talk about goblins”

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