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  5. GPT-6 SolvsMistral Large
Updated Sep 2026

GPT-6 SolvsMistral Large

GPT-6 Sol is cheaper than Mistral Large at $2/M vs $8/M input tokens.

GPT-6 Sol and Mistral Large compared across 20 shared prompts
SpecGPT-6 SolMistral Large
Input price$2/M tokens$8/M tokens
Output price$10/M tokens$24/M tokens
Context window1.1M tokens32K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 2026Feb 2024
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

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…

GPT-6 Sol937 words
Tidal Orchard Seared scallops · strawberry–kombu gel · white-miso and white-chocolate beurre blanc · sea-lettuce oil · buckwheat lace The unexpected pairing is scallop and strawberry. Both have a gentle sweetness, but strawberry’s acidity makes the scallop taste more distinctly of the sea.
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Mistral Large1,349 words
Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.
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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…

GPT-6 Sol90 words
Smoky Sunset Chickpeas Prep: 5 minutes · Cook: 15 minutes · Serves: 2 Ingredients 1 can chickpeas, drained 1 can diced tomatoes 1 tablespoon olive oil 2 garlic cloves, minced 1 teaspoon dried oregano ½ teaspoon smoked paprika ½ teaspoon salt Instructions Heat the olive oil in a skillet over medium heat.
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Mistral Large381 words
Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…
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…

GPT-6 Sol617 words
Experienced software engineer Think of a language model as a service whose API accepts a sequence of tokens and returns a probability distribution over the next token. During training, it sees enormous numbers of text sequences and adjusts billions of parameters to make the tokens that actually followed more likely.
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Mistral Large1,036 words
1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is computed.
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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.…

GPT-6 Sol245 words
Weak claim Why it’s weak How to strengthen it “Decode neural patterns into text with 94% accuracy. Works with any language, any device.” “Accuracy” has no defined unit: characters, words, or selecting from a small set of prompted phrases could produce very different results.
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Mistral Large920 words
Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…
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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) –…

GPT-6 Sol396 words
HarborTech Services — 5-year LBO Entry funding ($m): Enterprise value is $1,440.0 (12.0 × $120.0 EBITDA), plus $28.8 of transaction fees. The $1,468.8 total is funded with a $480.0 Term Loan, $180.0 of mezzanine debt, and $808.8 of equity.
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Mistral Large643 words
1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…
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Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

GPT-6 Sol1,402 words
A 12-week longevity and performance plan The highest-confidence longevity strategy is not a large supplement stack. It is consistent sleep, resistance training, aerobic fitness, adequate nutrition, cardiometabolic risk management, and avoiding tobacco.
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Mistral Large313 words
3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…
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Our Verdict
GPT-6 Sol
GPT-6 Sol
Mistral Large
Mistral LargeRunner-up

Not enough votes to call it. On the specs, GPT-6 Sol has the edge: newer, bigger context window, major provider backing.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-6 Sol
Input
$2.00
4.0× cheaper
Output
$10.00
2.4× cheaper
Mistral Large
Input
$8.00
Output
$24.00

GPT-6 Sol is cheaper on both: 4.0× input, 2.4× output.

Where to run it

4 hosts, cheapest first

GPT-6 Sol3 hosts
HostInOutContextUptime
Azure AI Foundry$2.00 in·$10.00 out·1.1M·96.6% upOpenAI$2.00 in·$10.00 out·1.1M·100% upAmazon Bedrock$2.20 in·$11.00 out·1.1M·99.9% up
Mistral Large1 host
HostInOutContextUptime
Mistral$2.00 in·$6.00 out·128k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

GPT-6 Sol is developed by OpenAI while Mistral Large is developed by Mistral AI. GPT-6 Sol has a 1.1M token context window vs Mistral Large's 32K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-6 Sol and Mistral Large each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.

GPT-6 Sol costs $2/M input tokens and Mistral Large costs $8/M input tokens. GPT-6 Sol is $6.00/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 GPT-6 Sol and Mistral Large 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

GPT-6 Sol logo
GPT-6 Sol20 outputs, specs and price
Mistral Large logo
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