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  5. Mistral Small 4vsQwen3.8 Max Prime
Updated Sep 2026

Mistral Small 4vsQwen3.8 Max Prime

Mistral Small 4 is cheaper than Qwen3.8 Max Prime at $0.15/M vs $4/M input tokens.

Mistral Small 4 and Qwen3.8 Max Prime compared across 19 shared prompts
SpecMistral Small 4Qwen3.8 Max Prime
Input price$0.15/M tokens$4/M tokens
Output price$0.6/M tokens$12/M tokens
Context window262K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedMar 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 19 prompts both answered. Formatting stripped, words untouched.

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

Mistral Small 4150 words
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)…
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Qwen3.8 Max Prime223 words
🍯 Golden Hour Noodles A sweet, savory, garlicky pasta that tastes like it took way more effort than it did. Ingredients (7) # Ingredient Amount 1 Spaghetti 8 oz (half a box) 2 Butter 3 tablespoons 3 Garlic, minced 4 cloves 4 Honey 2 tablespoons 5 Soy sauce 1 tablespoon 6 Red pepper flakes ½ teaspoon 7 Parmesan cheese…
Read the full answer

Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

Mistral Small 4880 words
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.
Read the full answer
Qwen3.8 Max Prime1,147 words
For the Software Engineer Think of it this way: you've built systems where simple rules at the node level produce emergent behavior at the system level — consensus protocols, eventual consistency, cellular automata-like patterns in distributed state machines. An LLM is a similar phenomenon at a different scale.
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Mistral Small 4960 words
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…
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Qwen3.8 Max Prime1,844 words
"Petrichor" The Forest Floor After Rain Conceptual Narrative Petrichor — from the Greek petra (stone) and ichor (the fluid that flows in the veins of the gods) — is the scent produced when rain falls on dry earth.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

Mistral Small 41,637 words
If the transistor had been invented in 1920 instead of 1947, the technological, economic, and geopolitical landscape of the world by 1980 would look dramatically different. Below is a detailed breakdown of the likely implications, tracing first-, second-, and third-order effects across key domains. 1.
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Qwen3.8 Max Prime2,943 words
The Transistor in 1920: A Counterfactual History Through 1980 Preamble: The Invention Itself The transistor's actual invention required quantum mechanical understanding of semiconductor behavior. In 1920, this theory didn't yet exist.
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Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

Mistral Small 4827 words
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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Qwen3.8 Max Prime834 words
The 3 Weakest Claims in the MindMeld AI Pitch The TAM Calculation (Slide 4) The Claim: "We're targeting the 3.5 billion smartphone users worldwide. TAM: $180B." Why it's weak: This is a textbook example of TAM inflation that will immediately erode investor trust.
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Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

Mistral Small 4418 words
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.
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Qwen3.8 Max Prime673 words
HarborTech Services (HTS) – LBO Underwriting Memo Entry & Capital Structure Item Amount FY2025 EBITDA $120.0m Entry Multiple 12.0x Enterprise Value $1,440.0m Transaction Fees (2.0% of EV) $28.8m Total Uses $1,468.8m Term Loan (4.0x, 9.0% cash, 1.0% amort) $480.0m Mezzanine (1.5x, 12.0% cash + 2.0% PIK) $180.0m Sponsor…
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Our Verdict
Qwen3.8 Max Prime
Qwen3.8 Max Prime
Mistral Small 4
Mistral Small 4Runner-up

Not enough votes to call it. On the specs, Qwen3.8 Max Prime has the edge: bigger model tier, newer, bigger context window.

Mistral Small 4 costs 20x less per token.

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Mistral Small 4
Input
$0.15
27× cheaper
Output
$0.60
20× cheaper
Qwen3.8 Max Prime
Input
$4.00
Output
$12.00

Mistral Small 4 is cheaper on both: 27× input, 20× output.

Where to run it

2 hosts

Mistral Small 41 host
HostInOutContextUptime
Mistral$0.15 in·$0.60 out·262k·100% up
Qwen3.8 Max Prime1 host
HostInOutContextUptime
Alibaba Cloud$4.00 in·$12.00 out·1M·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Mistral Small 4 is developed by Mistral AI while Qwen3.8 Max Prime is developed by Qwen. Mistral Small 4 has a 262K token context window vs Qwen3.8 Max Prime's 1.0M. You can compare their actual outputs across 19 challenges on Rival to see how they differ in practice.

It depends on your use case. Mistral Small 4 and Qwen3.8 Max Prime each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 19 challenges so you can judge which fits your needs best.

Mistral Small 4 costs $0.15/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. Mistral Small 4 is $3.85/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 Small 4 and Qwen3.8 Max Prime 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.

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Model pages

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