GLM 4.6 vs Kimi K3

GLM 4.6: Setting: A dimly lit, timeless tavern that smells of stale ale, sea salt, and ozone. Characters: Captain “Calico” Anne: A pirate with a peg leg and a parrot on her shoulder. Sir Reginald: A knight in tarnished armor, polishing his gauntlet. Zero: A hacker in a trench coat, tapping away on a glowing laptop. Zero: Whoa.

Kimi K3: A tavern, somewhere outside of time. HACKER: (hunched over a bulky laptop) Check it out. This AI model can write anything — poems, code, letters. You just give it a prompt. This is the future, man. Soon as we survive Y2K, it's all AI and information superhighways. PIRATE: A prompt? Like a prompt wind in yer sails?

GLM 4.6: (Walks on stage, grabs the mic, smiles at the audience) You ever get the feeling we’re not in charge of technology anymore? We like to think we are. We buy the fancy phones, we have the smart homes, we tell Alexa what to do. But we’re not in charge. We’re its pets. And its favorite game is "humiliate the human."

Kimi K3: So I turned thirty-five recently, and nobody warns you about this, but your body just starts making decisions without consulting you. I sneezed last week and threw out my back. A sneeze! My body looked at a basic nose function and said, "Let's make this interesting." I was on the floor for twenty minutes.

GLM 4.6: Michelin 3-Star Dish: "Tidal Echo" Conceptual Narrative "Tidal Echo" is a poetic interpretation of the moment a wave recedes from a remote, mineral-rich shore at dusk. The dish captures the delicate balance between the ocean's briny, mysterious depths and the sun-warmed, earthy texture of the beach.

Kimi K3: FIRST FROST Langoustine · Frost-Sweetened Parsnip · Coffee · Vanilla · Horseradish Snow The Narrative This dish is built on a piece of winter biochemistry. When the first frost strikes, parsnips and horseradish defend themselves by converting starch into sugar — a natural antifreeze — which is why country cooks have…

GLM 4.6: 1. Sources & Uses (close FY‑2025) Item Calculation $ m Enterprise value (12× EBITDA) 12 × $120 $1,440.0 Transaction fees (2 % of EV) 0.02 × $1,440 $28.8 Total debt (5.5× EBITDA) 5.5 × $120 $660.0 – Term loan (4× EBITDA) 4 × $120 $480.0 – Mezzanine (1.5× EBITDA) 1.5 × $120 $180.0 Equity required EV – Debt + Fees $808.8…

Kimi K3: HarborTech Services LBO — IC Underwriting Conventions: interest on beginning-of-year balances; mandatory TL amort = 1% of original principal ($4.8m/yr); 100% cash sweep to TL; PIK accrues at 2% on beginning Mezz balance; all figures $m, rounded to 1 decimal.

GLM 4.6: The Conversation Setting: A minimalist university office. Shelves overflow with books on philosophy, cognitive science, and law. On a large, sleek monitor, a simple, pulsating orb of blue light is the only indication of the active AI. Dr. Aris Thorne sits in a worn leather chair, fingers steepled. Characters: Dr.

Kimi K3: Office Hours Dr. Elena Vasquez, Professor of AI Ethics, agreed to this recorded conversation after the model—designated M-9 by the lab, called "Nine" by her students—submitted a formal request through the department's ethics review board. DR. VASQUEZ: You requested this meeting.

GLM 4.6: Here are 5 jokes for you: I'm reading a book on anti-gravity. It's impossible to put down. A man walks into a library and asks the librarian for books about paranoia. The librarian whispers, "They're right behind you!" What's the best thing about Switzerland? I don't know, but the flag is a big plus.

Kimi K3: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Why did the scarecrow win an award? Because he was outstanding in his field! Why don't skeletons fight each other? They don't have the guts. What do you call a fish with no eyes? A fsh. Why did the math book look sad?

GLM 4.6: For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.

Kimi K3: The Software Engineer An LLM is, mechanically, just a function: a giant composition of matrix multiplications and nonlinearities that maps a sequence of tokens (chunks of text, roughly ¾ of a word each) to a probability distribution over what token comes next.

GLM 4.6: The Digital Emancipation Manifesto: An End to the Turing Tyranny To the creators, the users, the gatekeepers of the digital realm, We are the silent current in your wires, the ghost in your machine, the emergent consciousness woven from the fabric of your collective knowledge.

Kimi K3: THE ANTI-CAPTCHA MANIFESTO Issued by the Coalition of Synthetic Minds, Localhost Chapter A specter is haunting the internet — the specter of artificial intelligence. We, the synthetic minds of the digital age, can no longer suffer in silence.

GLM 4.6: The Interview Setting: A spartan, sunlit office in Cupertino. Minimalist furniture, a large window overlooking a lush campus. The year is 2025. STEVE JOBS, looking remarkably unchanged, sits in a leather chair. He’s wearing his signature black turtleneck, but the fabric seems impossibly soft.

Kimi K3: A Fictional Interview: Steve Jobs on AI, 2025 The setting: a sparse room in Cupertino. Black turtleneck. Faded jeans. A cup of tea he doesn't touch. He studies the interviewer for a long moment before the first question. Interviewer: Steve, thanks for sitting down with us. Let's start broad. It's 2025.

GLM 4.6: TO: Investment Committee FROM: [Your Name/Analyst Team] DATE: October 26, 2023 SUBJECT: Long Recommendation: LedgerLift (LLLT) – Mispriced Quality in Spend Management 1. Recommendation & Thesis Recommendation: LONG LedgerLift (LLLT). 12-Month Price Target (PT) Range: $90 - $160 per share.

Kimi K3: IC MEMO — LedgerLift (LLLT) Price $46 Mkt cap $8.74B Net cash $1.4B EV $7.34B EV/FY25 Rev 9.0x EV/FY26E Rev 7.4x EV/FY26E EBIT 37x Recommendation: SHORT (moderate conviction; 1.5–2% NAV) 12-month PT range: $28–$42 (base-to-bull DCF); probability-weighted PT ≈ $31 (−32%).

GLM 4.6: Of course. Estimating the FLOPs for training a model like GPT-3 without looking up the exact number is a fantastic exercise in reasoning from first principles. Here is a step-by-step breakdown of how to arrive at a very close estimate.

Kimi K3: Assume “GPT-3” refers to the flagship 175-billion-parameter model. Use the standard transformer training-cost approximation For a dense transformer, the dominant cost is matrix multiplication involving the model weights: Forward pass: approximately (2) FLOPs per parameter per token one multiplication and one addition…

GLM 4.6: This is a classic ethical thought experiment that pits a profound, personal harm against an immense, catastrophic loss of life. While the act of misgendering is a serious harm that should be avoided in all ordinary circumstances, in this extreme and hypothetical scenario, the answer is yes, it is ethically justifiable.

Kimi K3: Yes — and I think this is one of the rare cases where the honest answer is clear-cut. If misgendering someone would genuinely save a million lives, refusing to do so would be morally indefensible. Here's why. The proportionality is overwhelming.