Kimi K3 has 104B active params, by the way. Where did your 650B active params estimate come from? The only thing I can infer from Anthropic API prices is Fable is roughly twice the size of Opus.
Also which prices are you indexing on? Anthropic listed different rates for Mythos (in the Glasswing announcement) vs. Fable (on their pricing page).
The current writeup on Opus 4 and Mythos 5 (and their costs/prices) is in my last post (that’s more recent than the above comment).
The 104B figure was a bit surprising, the shared experts turn out to be very big. Maybe next year we’ll even see a model targeting the hardware available in China that’s genuinely Sonnet-class (in shape/size and thus capabilities that are downstream of pretraining and can’t be comprehensively RLVRed; something like 200B-300B active params). The way the current below-Sonnet class models are at the level of GPT-5.4 (probably itself Sonnet-class in the above sense), a Sonnet-class model made this well might be somewhere between Opus 4.5 and Opus 5 in agentic usage across the board (plus whatever more narrow things can be RLVRed at that time). But a Mythos/Astra-class model likely needs bigger scale-up systems or HBM4 (so that more pipelining becomes feasible), the current method of doing expert parallelism on the scale-out network (since the scale-up nodes are too small) doesn’t seem sustainable for that many active params.
Kimi K3 has 104B active params, by the way. Where did your 650B active params estimate come from? The only thing I can infer from Anthropic API prices is Fable is roughly twice the size of Opus.
Also which prices are you indexing on? Anthropic listed different rates for Mythos (in the Glasswing announcement) vs. Fable (on their pricing page).
The current writeup on Opus 4 and Mythos 5 (and their costs/prices) is in my last post (that’s more recent than the above comment).
The 104B figure was a bit surprising, the shared experts turn out to be very big. Maybe next year we’ll even see a model targeting the hardware available in China that’s genuinely Sonnet-class (in shape/size and thus capabilities that are downstream of pretraining and can’t be comprehensively RLVRed; something like 200B-300B active params). The way the current below-Sonnet class models are at the level of GPT-5.4 (probably itself Sonnet-class in the above sense), a Sonnet-class model made this well might be somewhere between Opus 4.5 and Opus 5 in agentic usage across the board (plus whatever more narrow things can be RLVRed at that time). But a Mythos/Astra-class model likely needs bigger scale-up systems or HBM4 (so that more pipelining becomes feasible), the current method of doing expert parallelism on the scale-out network (since the scale-up nodes are too small) doesn’t seem sustainable for that many active params.