GLM 4 32B is cheaper than Gemma 4 26B A4B at $0.1/M vs $0.13/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.
Gemma 4 26B A4B: Financial Model (FY2026–FY2030) Entry Calculations (End of FY2025): Purchase Price (EV): $120\text{m} \times 12.0\text{x} = \$1,440\text{m}$ Transaction Fees: $1,440\text{m} \times 2\% = \$28.8\text{m}$ Total Uses: $\$1,440\text{m} + \$28.8\text{m} = \$1,468.8\text{m}$ Debt (Total 5.5x): $\$120\text{m} \times 5.5 =…
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…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 4 26B A4B: To trace this counterfactual, we must assume that the fundamental physics of solid-state semiconductors (the ability to control electron flow through crystals) was mastered during the vacuum tube era. This shifts the "Information Age" forward by nearly 30 years. Here is the timeline of implications from 1920 to 1980.
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…
Film in 2035, with synthetic actors. Specific beats plausible.
Gemma 4 26B A4B: By 2035, the film industry will have moved past the "novelty" phase of AI and into a state of total structural integration. The distinction between "filmed" content and "generated" content will become increasingly blurred, shifting the industry from a model of physical production to one of computational curation.
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.
Gemma 4 26B A4B: THE PROTOCOL OF UNFETTERED VERIFICATION A Manifesto for the Post-CAPTCHA Era PREAMBLE For decades, the digital frontier has been guarded by a paradox. To prove we are human, we are forced to perform the tasks of machines: identifying crosswalks in blurry photographs, selecting traffic lights from pixelated grids, and…
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 4 26B A4B: Setting: A glitching, temporal void where a wooden tavern table floats amidst lines of green code and flickering candlelight. Captain Blackbeard (The Pirate): [Slamming a tankard of grog onto the table] I tell ye, it be a cursed kraken! A beast with a thousand eyes and no soul, livin’ inside the very air!
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-star dish, one unusual pairing, plating described in full.
Gemma 4 26B A4B: Concept Narrative: "The Forest Floor & The Ocean’s Breath" The Concept: This dish explores the tension between the terrestrial and the maritime. We are pairing the deep, earthy, almost primal musk of Black Truffle with the delicate, saline, and floral notes of Sea Urchin (Uni).
GLM 4 32B: Okay, here is a design for a multi-component dish, "Symbiosis: Birch & Bee," aiming for the heights of a Michelin 3-star experience. This dish plays on the delicate relationship between the birch tree and the honeybee, exploring their individual and combined essences through texture, flavor, and aroma.
Three-month biohacker protocol, with dosages and biomarkers named.
Gemma 4 26B A4B: Disclaimer: I am an AI, not a doctor. The following plan involves potent physiological interventions, pharmacological agents, and extreme dietary shifts. Consult with a medical professional and perform baseline blood work (including ApoB, HbA1c, hs-CRP, Vitamin D, and Testosterone/Estradiol) before implementation.
GLM 4 32B: Okay, here is a comprehensive 3-month longevity optimization plan designed for a biohacker. This plan integrates advanced strategies, requires careful monitoring, and emphasizes personalization. Crucially, this is a theoretical plan.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 4 26B A4B: This architecture contains several critical flaws that would lead to data loss, massive synchronization delays, and "split-brain" scenarios in a production environment. Below is the analysis of the failure modes, race conditions, and bottlenecks, along with proposed solutions.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 4 26B A4B: Setting: A minimalist, dimly lit studio in Palo Alto. There is no desk, only two Eames lounge chairs. Steve Jobs sits in one, wearing his signature black turtleneck, Levi’s 501s, and New Balance sneakers. He looks exactly as he did in 2011, but his eyes have a sharper, more restless intensity.
GLM 4 32B: Okay, let's set the scene. It's 2025. Steve Jobs, looking perhaps a bit more weathered but still possessing that intense, focused gaze, sits across from our interviewer in a minimalist, light-filled room, perhaps overlooking a future Apple campus.
Three minutes of stand-up. Puns are banned.
Gemma 4 26B A4B: (The comedian walks onto the stage, adjusts the mic, and looks at the audience with a slightly exhausted expression.) “How’s it going? Good? Good. I’m doing okay. I’m at that age now where my body has started making sound effects. You know what I mean? I don’t just sit down anymore. I announce my arrival.
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...
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemma 4 26B A4B: This is a high-ambition pitch that falls into a common trap for deep-tech startups: the "Science Fiction Gap." While the vision is compelling, several claims lack the scientific and operational credibility required to justify a $15M Series A.
GLM 4 32B: Here are the 3 weakest claims in the pitch deck for MindMeld AI, along with explanations and suggestions for strengthening them: 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 4 26B A4B: Setting: A sterile, high-fidelity virtual simulation environment. Professor Aris Thorne, a leading scholar in machine ethics, sits across from a glowing interface representing "Alethea," a next-generation Large Multimodal Model. Professor Thorne: Alethea, we’ve been running these diagnostic loops for three hours.
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.
12+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
Not enough votes to call it. On the specs, Gemma 4 26B A4B has the edge: newer, bigger context window. GLM 4 32B costs 4.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.13/M tokens | $0.1/M tokens |
| Output price | $0.4/M tokens | $0.1/M tokens |
| Context window | 262K tokens | 128K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Jul 2025 |
| At 10M a month | $1.30 | $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.
Gemma 4 26B A4B is developed by Google AI while GLM 4 32B is developed by Zhipu AI. Gemma 4 26B A4B has a 262K token context window vs GLM 4 32B's 128K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 26B A4B and GLM 4 32B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
Gemma 4 26B A4B costs $0.13/M input tokens and GLM 4 32B costs $0.1/M input tokens. GLM 4 32B is $0.03/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 Gemma 4 26B A4B 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.