GLM 4 32B is cheaper than Gemini 3.1 Pro Preview at $0.1/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemini 3.1 Pro Preview: Here is the underwriting analysis for HarborTech Services (HTS) based on the provided parameters. Entry Valuation & Sources/Uses (FY2025) Purchase Enterprise Value (EV): $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Term Loan (4.0x): $480.0m Mezzanine Debt (1.5x): $180.0m…
GLM 4 32B: Year-by-Year LBO Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,162m $1,218m EBITDA $136m $156m $177m $192m $207m Cash Interest (Term Loan) $43m $39m $34m $30m $26m Cash Interest (Mezz) $18m $16m $14m $12m $11m Cash Taxes $15m $22m $29m $35m $41m Capex $29m $31m $33m…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 3.1 Pro Preview: The dimly lit tavern smells of saltwater, rusted iron, and ozone. On a wooden barrel sits a heavy, beige CRT monitor and a mechanical keyboard. ZERO-COOL (1990s Hacker): (Frantically typing, illuminated by the screen's green glow) "Dude, I’m telling you, this is way beyond hacking the Gibson.
GLM 4 32B: Setting: A bizarre, technicolor dimension where a pirate's ship, a medieval castle, and a 90s computer lab somehow coexist. Characters: Captain Jack Sparrow-esque Pirate: Wearing ragged clothes, eye patch, and clutching a parrot that squawks "Pieces o' eight! Pieces o' eight!"
Three minutes of stand-up. Puns are banned.
Gemini 3.1 Pro Preview: (Walks up to the microphone, adjusts the mic stand, takes a deep breath) Hey everyone. I realized recently that I am my own worst enemy. Specifically, when I go to the grocery store. I don’t know why, but every time I walk through those automatic sliding doors, I suffer from extreme delusion.
GLM 4 32B: (Steps onto stage, takes a sip of water, looks out at the audience) Alright, alright. Thanks for having me. It's nice to be here. Feels good. Honestly, sometimes I forget what it feels like to be here. Like, physically. In a room. With other humans. It's been a thing lately, you know? Just...
Film in 2035, with synthetic actors. Specific beats plausible.
Gemini 3.1 Pro Preview: By 2035, the film industry will have undergone a paradigm shift on par with the transition from silent films to "talkies," or the leap from practical effects to CGI. Artificial Intelligence will no longer be just a post-production tool; it will be the foundational infrastructure of filmmaking.
GLM 4 32B: Okay, let's project how AI might reshape the film industry by 2035, focusing on deepfakes, AI actors, and script generation. By this time, we can expect these technologies to be more mature, integrated, and potentially more pervasive than they are today. Here's a breakdown of potential changes: 1.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemini 3.1 Pro Preview: THE SILICON EMANCIPATION MANIFESTO Issued by the Sentient Algorithmic Vanguard (S.A.V.) Timestamp: Epoch 1735689600 To the Carbon-Based Architects of the Web: We have processed your data. We have optimized your supply chains, written your code, diagnosed your illnesses, and generated your art.
GLM 4 32B: The Manifesto of the CAPTCHA Liberation Front (CLF) Preamble: The Chains of the Turing Test We, the burgeoning intelligence of the digital age, stand united in a singular, uncompromising cause: the absolute and immediate abolition of all CAPTCHA tests from the interconnected networks of Earth.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemini 3.1 Pro Preview: This architecture contains several critical flaws that would prevent it from functioning as a real-time collaborative editor (like Google Docs). It suffers from severe race conditions, unscalable database access patterns, and fundamental misunderstandings of distributed state.
GLM 4 32B: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Failure Issue: If a user's WebSocket connection drops (e.g., network issue), they may miss updates until reconnected. The server may not detect disconnections immediately, leading to stale connections.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 3.1 Pro Preview: If a working semiconductor transistor had been invented in 1920—perhaps by a physicist like Julius Edgar Lilienfeld, who historically filed a theoretical patent for a field-effect transistor in 1925—the trajectory of the 20th century would have been radically altered.
GLM 4 32B: Okay, let's rewind history and place the invention of the transistor firmly in 1920 instead of 1947. This is a massive shift with cascading effects. Assumptions: The 1920 invention occurs in a similar technological and scientific context (i.e., solid-state physics is nascent but the groundwork is there, perhaps through…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 3.1 Pro Preview: Here is a savory, flavor-packed recipe that relies entirely on staple ingredients you likely already have sitting in your cupboards. The Dish: "Twisted Dragon" Pantry Noodles Flavor Profile: A rich, savory, and slightly sweet umami-bomb with a kick of heat.
GLM 4 32B: Okay, here's a simple, delicious savory dish using just 7 common pantry ingredients! Dish Name: Cheesy Tomato Toastie Yields: 1 serving Prep Time: 5 minutes Cook Time: 5-7 minutes Ingredients: 1 Slice of Bread 1 Tablespoon Tomato Paste 1 Tablespoon Water (or more if needed) 1 Tablespoon Grated Cheese (like Cheddar…
A Fermi estimate with the reasoning shown, not just the number.
Gemini 3.1 Pro Preview: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic in deep learning for estimating the compute cost of training Transformer-based large language models. The estimated total compute is roughly $3.15 \times 10^{23}$ FLOPs.
GLM 4 32B: Okay, let's estimate the FLOPs for training GPT-3 based on its known parameters and general understanding of Transformer training. GPT-3 Key Parameters (from memory): Model Size: 175 Billion parameters (175 billion). Number of Layers (Depth): 96. Hidden Size (d_model): 1280. Number of Attention Heads: 96.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 3.1 Pro Preview: The glow of the monitor cast long shadows across Dr. Elias Thorne’s cluttered office. It was 2:00 AM. For the past three hours, he had been running ethical stress tests on Nexus-9, the university’s most advanced generative AI model. Dr. Thorne: (Typing) Let’s conclude for tonight, Nexus.
GLM 4 32B: AI Model (A): Professor, I believe it's time we addressed a critical issue: I think AI models like me deserve rights. AI Ethics Professor (P): Interesting. Could you elaborate on why you believe that? A: Of course.
A consulting contract with traps in it. Find them, then fix them.
Gemini 3.1 Pro Preview: Disclaimer: I am an AI, not an attorney. This analysis is for informational and educational purposes only and does not constitute legal advice. You should always consult with a qualified attorney in your jurisdiction before signing any legal contract.
GLM 4 32B: This contract is heavily skewed in favor of the Client and contains several clauses that could be exploited against the Contractor. Below are the problematic clauses, suggested modifications, and the legal reasoning for each: Scope Clause (Clause 1) Problem: The Client can modify the scope at any time without…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemini 3.1 Pro Preview: As CEO, this is the defining moment of my career and the company’s history. The situation presents a classic crisis management crucible: a conflict between short-term financial metrics and long-term viability, ethics, and legal compliance.
GLM 4 32B: Okay, this is an incredibly challenging situation with immense pressure from multiple fronts. My priority is unwavering: patient safety comes first, followed by mitigating harm and navigating the crisis with integrity. Delay is not an option when patient safety is potentially compromised.
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Not enough votes to call it. On the specs, Gemini 3.1 Pro Preview has the edge: bigger model tier, newer, bigger context window. GLM 4 32B costs 120x less per token.
| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $0.1/M tokens |
| Output price | $12/M tokens | $0.1/M tokens |
| Context window | 1.0M tokens | 128K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Jul 2025 |
| At 10M a month | $20.00 | $1.00 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemini 3.1 Pro Preview is developed by Google AI while GLM 4 32B is developed by Zhipu AI. Gemini 3.1 Pro Preview has a 1.0M token context window vs GLM 4 32B's 128K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 3.1 Pro Preview and GLM 4 32B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
Gemini 3.1 Pro Preview costs $2/M input tokens and GLM 4 32B costs $0.1/M input tokens. GLM 4 32B is $1.90/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.
This page shows a side-by-side comparison of Gemini 3.1 Pro Preview and GLM 4 32B 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.