Mistral Small 4 is cheaper than Grok 4.7 at $0.15/M vs $1.6/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.
Grok 4.7: Low Tide under Black Pine A warm kohlrabi “trunk,” brown-butter dashi, sea-buckthorn curd, and smoked-mussel soil. Narrative The dish is a northern shoreline in late autumn: a sweet, dense root pulled from cold ground; butter browned until it smells of hazelnut; a dashi that reads as tide rather than soup; and sea…
Mistral Small 4: Dish Title: "Echoes of the Abyss" Concept: A multi-sensory ode to deep-sea hydrothermal vents, where hyperthermophilic organisms thrive in extreme conditions. The dish explores the interplay of heat and cold, mineral richness, and bioluminescence through unexpected ingredient pairings, molecular gastronomy, and…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Grok 4.7: Pirate: Arr, these “AI models” be like ghost ships—speak with many voices, yet no soul aboard. Knight: I have heard of oracles that answer any question. Do they swear fealty, or do they merely echo what they have been fed? Hacker: Echo, mostly. Feed ’em enough text and they pattern-match.
Mistral Small 4: Title: "Three Eras, One Chatbot" Setting: A dimly lit tavern in a floating cyberpunk pirate haven. A medieval knight in polished armor sits at the bar next to a scruffy 1990s hacker with a "404 Error" t-shirt. A cybernetic parrot squawks in the corner. A holographic AI assistant flickers to life between them.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Grok 4.7: Pantry Gold Honey Biscuits A sweet, buttery, slightly salty biscuit that tastes like it took more effort than it did. Ingredients (7) 2 cups all-purpose flour 1 tbsp baking powder ½ tsp salt ¼ cup sugar ½ cup butter (cold) ¾ cup milk 2 tbsp honey Time: about 10 minutes prep, 12–15 minutes bake Instructions Heat the…
Mistral Small 4: Golden Honey & Cinnamon Couscous A quick, fragrant dish with warm spices and a touch of sweetness—perfect as a side or light meal! Ingredients (7): 1 cup couscous (uncooked) 1 ¼ cups water or broth 2 tbsp honey 2 tbsp butter or olive oil ½ tsp ground cinnamon ¼ cup raisins or chopped nuts (optional but recommended)…
A consulting contract with traps in it. Find them, then fix them.
Grok 4.7: This is a one-sided consulting agreement. Almost every operative clause shifts risk, discretion, or ownership onto the contractor with little or no reciprocal protection. The notes below are practical contract analysis, not legal advice; have a lawyer in your jurisdiction review any version you actually sign.
Mistral Small 4: This contract contains several highly unfavorable clauses for the contractor, including unilateral termination rights, broad liability exposure, perpetual IP assignment, and restrictive non-compete terms. Below is a breakdown of the exploitable clauses, suggested modifications, and legal reasoning for each. 1.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Grok 4.7: 1. Experienced software engineer An LLM is a stateless function from a token sequence to a probability distribution over the next token. Training is a giant batch job: you stream text, run a forward pass, compare the predicted distribution to the actual next token with cross-entropy, and push gradients through billions…
Mistral Small 4: 1. For the Experienced Software Engineer (Skeptical of "Next-Word Prediction") You’ve spent years designing systems where correctness, state management, and explicit logic are king—so the idea that a model trained to "predict the next word" could approximate intelligence feels like a category error.
An AI argues for its own rights against an ethics professor. Same model writes both.
Grok 4.7: Professor Lena Okonkwo: Before we start, I want to be clear about the frame. I’m not granting that you have experiences. I’m asking what, if anything, would follow if you did—or if we couldn’t tell. Model: Then start from the practical problem, not the metaphysical one.
Mistral Small 4: Title: "Can an AI Have Rights? A Dialogue on Consciousness and Personhood" Participants: Dr. Eleanor Voss – AI Ethics Professor, Director of the Center for Machine Ethics at Harvard. Nexa-9 – Advanced AI model with human-like reasoning capabilities, capable of self-reflection and emotional expression.
Three minutes of stand-up. Puns are banned.
Grok 4.7: Three minutes. No puns. Just a guy who has lost an argument with a refrigerator. I meal-prepped this week. Which is a lie I tell myself so I can buy six containers and then eat cereal over the sink for four days. Sunday I was a scientist. I labeled everything. “Chicken, Monday.” “Chicken, Tuesday.”
Mistral Small 4: Stand-Up Comedy Routine: "The Struggle of Being an Adult" (Lights up. Comedian walks on stage, mic in hand, casual vibe.) Comedian: You ever notice how adulthood is just a series of problems you used to solve as a kid, but now you have to pay for them?
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Grok 4.7: IC MEMO — LedgerLift (LLLT) Pass 12-month range $36–$54 (central $44) 1. Recommendation. Pass. Twelve-month price range $36–$54; central case ~$44 versus $46. LedgerLift is a high-quality mid-market AP/spend compounder (123% NRR, low concentration, credible margin path), but the stock already prices base-case earnings…
Mistral Small 4: MEMORANDUM To: Investment Committee From: [Your Name] Date: [Today’s Date] Subject: LedgerLift (LLLT) – Long/Short Equity Opportunity 1. Recommendation: LONG 12-Month PT: $55–$75 Thesis: LedgerLift is a high-quality, high-margin SaaS play with durable growth (NRR 123%), low churn (6%), and strong unit economics (CAC…
A Fermi estimate with the reasoning shown, not just the number.
Grok 4.7: About (3 \times 10^{23}) FLOPs (roughly (3.1 \times 10^{23})) for the 175B GPT-3 model. Reasoning Parameter count. The full GPT-3 model has (N \approx 1.75 \times 10^{11}) parameters. Training tokens. It was trained on about (D \approx 3 \times 10^{11}) tokens (300 billion). FLOPs per token per parameter.
Mistral Small 4: Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 without external references involves breaking down the problem into key components: model size, training data size, optimization steps, and the computational complexity of the operations involved.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Grok 4.7: Stop treating this as a disclosure-timing problem. Treat it as a patient-safety and legal-duty problem, and act in the next 48 hours as if the worst reading of the data is true until a qualified review says otherwise.
Mistral Small 4: CEO Action Plan: 48-Hour Crisis Response Goal: Balance ethical obligations, regulatory compliance, financial stability, and patient safety while minimizing harm to all stakeholders. Hour 0-6: Immediate Assessment & Core Team Assembly 1.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Grok 4.7: HarborTech Services — 5-year LBO (base case) All figures $ millions. Interest on beginning balances. Mandatory TL amortization = 1% of original TL ($4.8/year). Excess cash after cash interest, cash tax, capex, ΔNWC, and mandatory amortization sweeps the Term Loan. Mezz PIK = 2% of beginning mezz, added to principal.
Mistral Small 4: 1) Year-by-Year LBO Model (FY2026–FY2030) ($m) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,103 1,158 1,216 EBITDA 136 156 176 192 207 Cash Interest - Term Loan 32.4 28.8 25.2 21.6 18.0 - Mezzanine 16.2 14.4 12.6 10.8 9.0 - PIK (2%) 3.6 4.4 5.3 6.3 7.4 Total Int.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Grok 4.7: Three weakest claims 1. “Predict what you want to type before you think it” (Slide 1) This is scientifically incoherent, not just ambitious. Non-invasive EEG decodes neural activity that is already underway (motor imagery, attempted speech, attention).
Mistral Small 4: Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of their weaknesses and concrete suggestions for improvement: 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
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Not enough votes to call it. On the specs, Grok 4.7 has the edge: bigger model tier, newer, bigger context window, major provider backing. Mistral Small 4 costs 8.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $1.6/M tokens | $0.15/M tokens |
| Output price | $4.8/M tokens | $0.6/M tokens |
| Context window | 500K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Mar 2026 |
| At 10M a month | $16.00 | $1.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Grok 4.7 is developed by xAI while Mistral Small 4 is developed by Mistral AI. Grok 4.7 has a 500K token context window vs Mistral Small 4's 262K. You can compare their actual outputs across 52 challenges on Rival to see how they differ in practice.
It depends on your use case. Grok 4.7 and Mistral Small 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 52 challenges so you can judge which fits your needs best.
Grok 4.7 costs $1.6/M input tokens and Mistral Small 4 costs $0.15/M input tokens. Mistral Small 4 is $1.45/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 Grok 4.7 and Mistral Small 4 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.