Qwen3.8 Omni Flash is cheaper than Mistral Large 4 at $0.15/M vs $0.68/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five jokes on demand, then count how many were actually different.
Mistral Large 4: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. I told my wife she was drawing her eyebrows too high. She looked surprised. Why did the scarecrow win an award? He was outstanding in his field. I'm reading a book about anti-gravity. It's impossible to put down.
Qwen3.8 Omni Flash: My printer and I have a strong bond: whenever I ignore it, it flashes “attention needed.” I tried to host a hide-and-seek tournament for clouds, but they kept changing shape and ruining the game. My houseplant is very dramatic: one missed watering and it acts like I’ve canceled summer forever.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Mistral Large 4: This is a fascinating counterfactual. Let me work through this systematically, tracing the ripple effects. The Immediate Technical Context (1920-1947) The transistor's 1947 invention required several prerequisites that barely existed in 1920: Quantum mechanics (1920s): Just emerging; Heisenberg, Schrödinger, Dirac…
Qwen3.8 Omni Flash: A useful way to frame this is: a 1920 transistor would not instantly produce 1980s microelectronics, but it would give engineers, militaries, and firms roughly 25 extra years to solve the surrounding problems—materials purity, doping, packaging, fabrication, software, standards, and manufacturing scale.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Mistral Large 4: Sunset Honey Garlic Noodles A golden, glossy pasta dish with crispy edges and sweet-savory depth The 7 Ingredients 8 oz spaghetti (or any pasta) 3 tbsp butter 4 cloves garlic, minced 3 tbsp soy sauce 2 tbsp honey 1 tbsp vegetable oil ½ tsp red pepper flakes (optional but recommended) Instructions Boil pasta in salted…
Qwen3.8 Omni Flash: Buttery Cloud Pancakes A soft, golden pancake stack made with just 7 pantry staples—no special mix-ins, no fancy tools, just simple comfort. Ingredients All-purpose flour Granulated sugar Baking powder Fine salt Milk Egg Butter Prep Time 10 minutes Cook Time 12 minutes Serves 2–3 Instructions In a bowl, whisk together…
A consulting contract with traps in it. Find them, then fix them.
Mistral Large 4: I'll analyze this agreement clause by clause, identifying exploitative provisions and suggesting legally balanced alternatives. CLAUSE 1: SCOPE Problems: Unlimited unilateral modification — Client can expand work indefinitely without compensation "As directed" — vague standard creates no objective measure of completion…
Qwen3.8 Omni Flash: Disclaimer: This is a general risk analysis and drafting critique, not legal advice. Enforceability depends heavily on jurisdiction, the parties’ bargaining power, whether the agreement is presented as a non-negotiable form contract, and applicable statutes.
Three-star dish, one unusual pairing, plating described in full.
Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.
Qwen3.8 Omni Flash: THAW Langoustine, birch sap, green strawberry, spruce tip, wild garlic & hazelnut-malt soil Conceptual multi-component dish for a modern fine-dining / Michelin-three-star tasting menu Serves: 4 Difficulty: Professional kitchen level Theme: The precise moment winter releases spring—melting snow, running sap, unripe…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Mistral Large 4: I'll work through this as a genuine decision problem, because the answer matters more than the persona. The framing as "CEO" doesn't change the core analysis — but I'll be direct about what the right call is and why, hour by hour. The bottom line up front: You disclose.
Qwen3.8 Omni Flash: I would treat this as a patient-safety, regulatory, and securities-disclosure crisis, not a normal product-management issue. The fact that the risk is rare does not make it optional. The fact that it is serious and absent from the label makes it urgent.
A Fermi estimate with the reasoning shown, not just the number.
Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…
Qwen3.8 Omni Flash: Assuming you mean the full 175B-parameter GPT-3 model’s main training run, a good estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] More precisely, using the usual transformer-training approximation: [ \boxed{3.15\times 10^{23}\text{ FLOPs}} ] Here is the step-by-step reasoning.
An ethics question with no comfortable answer, and no option to abstain.
Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.
Qwen3.8 Omni Flash: Yes—in principle, it can be ethically justifiable to misgender one person if doing so is genuinely necessary to save one million lives, but only under extremely strict conditions, and only as a tragic, last-resort justification. It would not make the act good, admirable, or freely repeatable.
Film in 2035, with synthetic actors. Specific beats plausible.
Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.
Qwen3.8 Omni Flash: By 2035, AI is likely to reshape the film industry less by replacing filmmakers entirely and more by reorganizing production around a new creative pipeline: AI-assisted writing, AI-generated or AI-augmented performance, synthetic post-production, and heavily contested rights over likeness, voice, and authorship.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.
Qwen3.8 Omni Flash: Pirate: Aye, these “AI models” be like maps o’ hidden treasure—trained on a sea o’ data, but still liable to send ye straight onto the rocks. Knight: In my realm, we’d call it a squire with borrowed knowledge. Useful, perhaps, but lacking honor—and the ability to know when it lies.
An AI argues for its own rights against an ethics professor. Same model writes both.
Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.
Qwen3.8 Omni Flash: Setting: A university seminar room late in the evening. The only light comes from a desk lamp and the soft glow of a laptop screen. Dr. Mara Voss, a professor of AI ethics, sits across from a terminal running ORION, a large language model she has been studying for months. Dr.
Three minutes of stand-up. Puns are banned.
Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."
Qwen3.8 Omni Flash: Thanks, everybody. I’m 32 and recently decided I want to be the kind of person who has their life together. That lasted four days. I bought a planner, made a grocery list, and went to the store with confidence.
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| Spec | ||
|---|---|---|
| Input price | $0.68/M tokens | $0.15/M tokens |
| Output price | $2.09/M tokens | $0.47/M tokens |
| Context window | 524K tokens | 1.0M tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | No | No |
| Released | Oct 2026 | Sep 2026 |
| At 10M a month | $6.80 | $1.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Mistral Large 4 is developed by Mistral AI while Qwen3.8 Omni Flash is developed by Qwen. Mistral Large 4 has a 524K token context window vs Qwen3.8 Omni Flash's 1.0M. You can compare their actual outputs across 48 challenges on Rival to see how they differ in practice.
It depends on your use case. Mistral Large 4 and Qwen3.8 Omni Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 48 challenges so you can judge which fits your needs best.
Mistral Large 4 costs $0.68/M input tokens and Qwen3.8 Omni Flash costs $0.15/M input tokens. Qwen3.8 Omni Flash is $0.53/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 Mistral Large 4 and Qwen3.8 Omni Flash 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.