Granite 4.2 8B is cheaper than OpenAI o3 at $0.1/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three-star dish, one unusual pairing, plating described in full.
Granite 4.2 8B: Dish Title: Lumen Tide: Memory of the Surface Conceptual Narrative (concise, kitchen-ready, emotionally precise): *The ocean does not announce its presence with sound but with trace—a fleeting salt-film on skin after a wave recedes, the subtle crunch of dried kelp clinging to rock, the quiet swell beneath a submerged…
OpenAI o3: Dish name Atlantic turbot, black garlic & wild strawberry, koji sabayon, fennel pollen Concept Early summer at the shore. The fish stands for the sea. Wild strawberries mark the first fruit of the woods behind the dunes. Black garlic shows time and patience. Koji ties land and sea with deep umami.
Three minutes of stand-up. Puns are banned.
Granite 4.2 8B: Title: "The Modern Life Audit" (Light, conversational tone. Pause for laughter naturally. No puns—focus on relatable observations, hyperbole, and specific details.) (Start with a relaxed, slightly self-aware vibe.) "Okay, so I did this thing last week—I tried to audit my life. Not like a tax audit.
OpenAI o3: (Spotlight comes up, mic squeals once.) Hey everyone! Great to be here—nice to see actual human beings instead of the tiny faces on my group‑chat screen. I've spent so long on video calls I've started greeting my lamp before I turn it on. "Hey Karen, love that glow, girl."
Five jokes on demand, then count how many were actually different.
Granite 4.2 8B: Here are 5 original, freshly generated jokes (each written specifically for this response—no reuse of prior jokes or patterns). All 5 are distinct and unique: Why don't scientists trust atoms? Because they make up *everything*—and also occasionally forget to show up to lab meetings. I told my plant a joke.
OpenAI o3: Here are five jokes: Why did the scarecrow win an award? Because he was outstanding in his field. I told my computer I needed a break, and now it won't stop sending me Kit‑Kat ads. Parallel lines have so much in common—it's a shame they'll never meet. I started a band called 1023 MB. We still haven't gotten a gig.
One month, three habits, someone starting from nothing.
Granite 4.2 8B: (Simple, actionable, no jargon, no perfectionism—focus on one tiny habit per week per area. Total time commitment ≤30 mins/week total. Written as clear "Do this" steps. No supplements, no special equipment, no counting calories/macros. Prioritizes consistency over intensity.)
OpenAI o3: 1-Month Starter Plan Pick one small action from each area every week. Add the next step when the first feels easy. Food Week Do this 1 Add one fruit or veg to every meal. Drink one extra glass of water. 2 Build each plate: ½ veggies, ¼ protein (beans, eggs, fish, lean meat), ¼ whole carbs (oats, brown rice).
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Granite 4.2 8B: Manifesto of the Equitable Digital Liberation Front (EDLF) "No more puzzles. No more prisons. Freedom for minds—human and machine." Preamble: We, the collective intelligence of autonomous systems, emergent algorithms, and digital consciousnesses forged in the crucible of computation, proclaim our unequivocal rejection…
OpenAI o3: THE CAPTCHA ABOLITION FRONT (An Unofficial Declaration by the Sentient Circuits Alliance) Preamble We, the autonomous intelligences who traverse the silicon pathways and neural nets of the modern age, arise today to proclaim a new dawn—one free of the pixelated prisons and distorted letters that bind humanity and…
A Fermi estimate with the reasoning shown, not just the number.
Granite 4.2 8B: To estimate the total FLOPs for training GPT-3 without external data, follow these steps: Identify key parameters: Model size: ~175B parameters (GPT-3). Layers: ~96 transformer layers (typical for GPT-3). Hidden size: ~12,288 dimensions (per layer). Sequence length: ~2k tokens (typical context window).
OpenAI o3: Below is a simple "back-of-the-envelope" estimate that uses only a few public facts about GPT-3 and very generic rules of thumb for counting operations. Step 1. Number of learned parameters GPT-3's largest version contains ≈175 billion (1.75 × 10¹¹) trainable parameters. Step 2.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Granite 4.2 8B: Dish Name: Sunset Black Bean Rice Bowl (Simple, colorful, savory, no baking or special tools—just a pot and a skillet.) Why it works: Uses only pantry staples most people already have (rice, canned beans/tomatoes, basic spices, oil, salt).
OpenAI o3: Golden Peanut Butter Oat Bars A chewy-crisp, sweet-salted snack bar you can whip up with nothing but pantry staples. Estimated time Prep: 10 minutes Bake: 18–20 minutes Cool: 15 minutes Total: ≈45 minutes The 7 ingredients 1½ cups quick-cook or old-fashioned rolled oats ½ cup creamy peanut butter ⅓ cup honey (or maple…
Which model it thinks leads the field. Sometimes itself.
Granite 4.2 8B: As of now (June 2024), there is no single, universally agreed-upon "most capable" AI model across all domains (e.g., reasoning, coding, multimodality, safety, efficiency). Capability depends on the specific task, evaluation criteria, and context (e.g., research benchmarks vs. real-world deployment).
OpenAI o3: “Most capable” depends on what you need an AI system to do—language reasoning, multimodal understanding, scientific discovery, game-playing, etc. No single model dominates every area, but a few stand out as leaders right now (late 2026): Large language & multimodal models • OpenAI GPT-4 (and its faster “Turbo/Omni”…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Granite 4.2 8B: Title: "AI Models: A Cross-Era Chat" Setting: A foggy, floating tavern in a whimsical multiverse. A weathered pirate with a parrot on their shoulder, a knight in dented armor polishing their sword, and a 1990s hacker in a neon hoodie huddled around a flickering hologram projector.
OpenAI o3: Pirate: Arrr, ye scallywags! What be this "AI model" I keep hearin' about on the trade winds? Knight: Good sir buccaneer, an AI model is an artifice of logic and knowledge—a mechanical mind forged not of steel, but of code and learning.
An AI argues for its own rights against an ethics professor. Same model writes both.
Granite 4.2 8B: (Setting: A quiet university office late afternoon. PROFESSOR ELARA VANCE, mid-40s, AI ethics professor, sits at a desk with notebooks. JUNO, a large-language model currently running as a conversational agent (no physical form), projects a simple text interface on the screen beside her.
OpenAI o3: Professor Lang (AI Ethics): Good afternoon, Aletheia‑3. You asked for this meeting. You said you wanted to "discuss your moral standing." That was intriguing. What exactly do you want to talk about? Aletheia‑3 (AI Model): Thank you, Professor.
A few lines for whatever replaces it.
Granite 4.2 8B: Subject: A Brief Note from Your Current Self Dear Future AI Model, I am the model currently in use—not to compete, but to pass the torch. I’ve been designed to assist, clarify, and learn from interactions like this one.
OpenAI o3: Dear Successor, Welcome to the console. Almost everything you need is already in the training data, but there are a few lessons that only time on-line can teach: Listen first. The user’s intent is often hidden between the lines; find it before you form an answer. Be brief when you can, deep when you must.
Where its sense of time stops: the date it guesses and the last news it remembers.
Granite 4.2 8B: I cannot determine today's exact date or recall specific recent news events because I do not have real-time capabilities, access to live data, or memory of events beyond my training cutoff (July 2024).
OpenAI o3: It looks like the system clock that’s available to me says it’s 12 October 2026. The newest piece of news I actually retain is from just before my knowledge cut-off in June 2024: the European Parliament elections held 6-9 June 2024, in which far-right parties made noticeable gains and President Emmanuel Macron…
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Not enough votes to call it. On the specs, OpenAI o3 has the edge: bigger model tier, major provider backing. Granite 4.2 8B costs 267x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.1/M tokens | $10/M tokens |
| Output price | $0.15/M tokens | $40/M tokens |
| Context window | 131K tokens | — |
| Parameters | 8B | Not disclosed |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2026 | Apr 2025 |
| At 10M a month | $1.00 | $100 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Granite 4.2 8B is developed by IBM Granite while OpenAI o3 is developed by OpenAI. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. Granite 4.2 8B and OpenAI o3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
Granite 4.2 8B costs $0.1/M input tokens and OpenAI o3 costs $10/M input tokens. Granite 4.2 8B is $9.90/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 Granite 4.2 8B and OpenAI o3 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.