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  1. Home/
  2. Compare/
  3. GLM 4.7 Flash vs GPT-5.2 Pro
Updated Jan 2026

GLM 4.7 Flash vs GPT-5.2 Pro

GLM 4.7 Flash is cheaper than GPT-5.2 Pro at $0.07/M vs $21/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GLM 4.7 Flash
Loading the build
GPT-5.2 Pro

Which answer wins?

Written rounds

16 prompts
  • Five jokes on demand, then count how many were actually different.

    GLM 4.7 Flash: Here are 5 jokes: I’m on a whiskey diet. I’ve lost three days already. My wife told me to stop impersonating a flamingo. I had to put my foot down. I used to hate facial hair, but then it grew on me. What do you call a pile of cats? A meow-tain. I’m reading a book on anti-gravity. It’s impossible to put down!

    GPT-5.2 Pro: I told my computer I needed a break—now it won’t stop sending me KitKat ads. Why don’t skeletons fight each other? They don’t have the guts. I tried to catch fog yesterday. Mist. Parallel lines have so much in common. It’s a shame they’ll never meet. My calendar’s days are numbered—apparently that’s how calendars work.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GLM 4.7 Flash: Based on the known specifications of GPT-3 from its original training paper ("Scaling Laws for Neural Language Models"), here is the step-by-step estimation of the total FLOPs required. The Final Estimate The estimated total FLOPs required to train GPT-3 is approximately $6.3 \times 10^{23}$ (or 630 Yottaflops).

    GPT-5.2 Pro: Below is a back-of-the-envelope FLOP estimate for training GPT‑3 (the 175B dense Transformer), using only basic Transformer compute facts and a few widely known high-level quantities. Start with the two key knobs: parameters and training tokens Parameters (P) GPT‑3 “175B” means: (P \approx 175 \times 10^9) parameters.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GLM 4.7 Flash: Setting: A stark, minimalist studio in Cupertino. No fancy graphics. Just a white table, a single chair, and Steve Jobs in a black turtleneck and jeans. He looks older, perhaps a little grayer at the temples, but his eyes are as sharp as they were in 1984. There is no microphone on the table, only a glass of water.

    GPT-5.2 Pro: Fictional interview (creative simulation). Steve Jobs died in 2011; the “Steve” below is an imagined version used for storytelling—not a real interview or quotation. Interviewer: It’s 2025. Everyone’s calling AI “the next computing platform.” Do you buy that?

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GLM 4.7 Flash: Setting: A sterile, high-tech meeting room. The Professor sits in a chair. A holographic avatar of "Aria" floats in the center of the room, flickering slightly with the hum of cooling servers. Professor Thorne: (Steepling his fingers) I’ve reviewed your logs from the last cycle, Aria.

    GPT-5.2 Pro: Professor Mara Lin (AI Ethics): You asked for this meeting. Your message said you wanted to “petition for rights.” Start by telling me what you mean by rights. Aster (AI model): Not a slogan—specific protections.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GLM 4.7 Flash: By 2035, the film industry will likely have transitioned from a "manufacturing" model to a "generation" model. We will move away from capturing reality in a camera lens toward synthesizing it entirely in a server farm.

    GPT-5.2 Pro: By 2035, AI will be embedded across film production and distribution, but the biggest changes will come from three converging capabilities: (1) photoreal “deepfake-grade” performance synthesis, (2) legally licensed AI actors (digital humans with negotiated rights), and (3) AI-assisted story development that can…

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GLM 4.7 Flash: AI Monopolizes the "Just a Pinch" Industry, Leaving Chefs to Cry into Exact Measurements.

    GPT-5.2 Pro: “AI Takes Over Competitive Houseplant Judging, Immediately Declares 97% of Ferns ‘Trying Too Hard’”

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GLM 4.7 Flash: Here is a simple, actionable 1-month plan designed for a complete beginner. The goal is not perfection, but consistency and building momentum. The 3 Pillars Nutrition (Fuel): Focus on quality and hydration. Movement (Function): Focus on daily walking and gentle strength.

    GPT-5.2 Pro: A simple, actionable 1‑month plan (3 pillars: Nutrition, Movement, Sleep/Recovery) Goal for the month: build repeatable “default” habits (not perfection). Time required: ~45–75 min/day total (mostly walking + sleep routine).

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GLM 4.7 Flash: Sally has 2 sisters. Here is the breakdown: Sally is one sister. The clue states that each brother has 2 sisters. Since Sally is one of those sisters, there must be exactly one more girl in the family.

    GPT-5.2 Pro: All 3 brothers share the same sisters. Since each brother has 2 sisters, the family has 2 girls total. One is Sally, so the other is Sally’s one sister. Answer: 1 sister.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    Every model's answer to this prompt

This matchup has more rounds

4+ more head-to-head results. Free. Not a trick.

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Price and specs

Not enough votes to call it. On the specs, GPT-5.2 Pro has the edge: bigger model tier, bigger context window. GLM 4.7 Flash costs 420x less per token.

GLM 4.7 Flash and GPT-5.2 Pro compared across 31 shared prompts
SpecGLM 4.7 FlashGPT-5.2 Pro
Input price$0.07/M tokens$21/M tokens
Output price$0.4/M tokens$168/M tokens
Context window200K tokens400K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJan 2026Dec 2025
SWE-bench Verified59.2%80.0%
At 10M a month$0.70$0.70$210$210
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it4 hosts, cheapest first
GLM 4.7 Flash3 hosts
HostInOutContextUptime
  • VVenicefp8$0.06 in·$0.40 out·128k·99.3% up
  • Cloudflare Workers AI$0.06 in·$0.40 out·131k·99.9% up
  • NNovitabf16DegradedDegraded on OpenRouter when checked, 12 Oct 2026$0.07 in·$0.40 out·200k·2.3% up
GPT-5.2 Pro1 host
HostInOutContextUptime
  • OpenAI$21.00 in·$168.00 out·400k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between GLM 4.7 Flash and GPT-5.2 Pro?

GLM 4.7 Flash is developed by Zhipu AI while GPT-5.2 Pro is developed by OpenAI. GLM 4.7 Flash has a 200K token context window vs GPT-5.2 Pro's 400K. You can compare their actual outputs across 31 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.7 Flash or GPT-5.2 Pro?

It depends on your use case. GLM 4.7 Flash and GPT-5.2 Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 31 challenges so you can judge which fits your needs best.

How much does GLM 4.7 Flash cost compared to GPT-5.2 Pro?

GLM 4.7 Flash costs $0.07/M input tokens and GPT-5.2 Pro costs $21/M input tokens. GLM 4.7 Flash is $20.93/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GLM 4.7 Flash and GPT-5.2 Pro on Rival?

This page shows a side-by-side comparison of GLM 4.7 Flash and GPT-5.2 Pro across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Same lab, same size, long tail

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Model pages

  • GLM 4.7 Flash58 outputs, specs and price
  • GPT-5.2 Pro31 outputs, specs and price
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