The trick: Zero Underneath
ByteDance is training a 10 trillion parameter model.
That number tells you almost nothing.
The Financial Times reported, citing three people, that ByteDance is pretraining a model with up to 10 trillion parameters to rival Anthropic's Mythos.
Before you read on. Your call?
TRUE, BUT
0 evals published
the report holds. Multiple outlets corroborate it. But 10 trillion is described as an upper bound still under consideration, not a final spec, and there are zero published evals. The 'rivals Mythos' line compares it to an unofficial 8 trillion estimate that Anthropic has never confirmed, because Anthropic does not publish parameter counts at all.
The twist
parameter count is not capability. Kimi K3 lists 2.8 trillion parameters but activates only 104 billion per token, and nobody has said whether ByteDance's number is dense or sparse. As one write-up put it, ten trillion is the upper bound of scale under consideration, not a finished performance benchmark. Bigger is bigger. It is not automatically better.
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The trick has a name
We call it Zero Underneath: the headline number has nothing behind it. You'll see it again. Learn to spot it →
Receipts
- Supports mlq.ai:
ByteDance is training an AI model with as many as 10 trillion parameters, the Financial Times reported Friday, citing three people familiar with the project
- Supports thenextweb.com:
the model is meant to rival Anthropic’s Mythos, one of the frontier systems that Chinese developers have so far struggled to match
- Context eweek.com:
Industry estimates place Anthropic’s advanced Mythos 5 model at roughly 8 trillion parameters, though Anthropic does not publish official parameter counts
- Refutes xenospectrum.com:
Ten trillion is not a finished performance benchmark
Open the Receipts Pack → What each source proves, every figure traced, and what would change our verdict.
