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  5. Gemini 2.5 Pro ExperimentalvsMistral Large
Updated Mar 2025

Gemini 2.5 Pro ExperimentalvsMistral Large

Gemini 2.5 Pro Experimental is cheaper than Mistral Large at $1/M vs $8/M input tokens.

Gemini 2.5 Pro Experimental and Mistral Large compared across 42 shared prompts
SpecGemini 2.5 Pro ExperimentalMistral Large
Input price$1/M tokens$8/M tokens
Output price$2/M tokens$24/M tokens
Context window1.0M tokens32K tokens
ParametersNot disclosedNot disclosed
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMar 2025Feb 2024
MMLU90.0%81.2%
Side by side

Same prompt, both answers

Opening lines from 6 of the 42 prompts both answered. Formatting stripped, words untouched.

Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

Gemini 2.5 Pro Experimental949 words
Okay, let's simulate this. Imagine it's late 2025. AI has continued its rapid advancement. Large Language Models are more integrated, generative AI is commonplace, and debates about AGI and ethics are fierce. By some unexplained, hypothetical means, Steve Jobs is available for an exclusive interview.
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Mistral Large1,143 words
Title: "The Future of AI: A Hypothetical Interview with Steve Jobs (2025)" Location: A minimalist, sunlit studio in Palo Alto. Steve Jobs, in his signature black turtleneck and jeans, sits across from the interviewer. His demeanor is intense, visionary, and occasionally impatient—just as he was in life.
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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…

Gemini 2.5 Pro Experimental977 words
Of course. Here is an explanation of how a large language model learns and generates text, tailored for each of your three audiences. For the Experienced Software Engineer Think of an LLM not as a traditional program with explicit logic, but as a massive, self-configuring, stateful distributed system.
Read the full answer
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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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…

Gemini 2.5 Pro Experimental349 words
Okay, here's a simple and surprisingly satisfying savory dish using just 7 common pantry staples! Dish Name: Golden Pantry Pasta This dish uses basic ingredients to create a comforting, garlicky, and slightly creamy pasta sauce with added protein from chickpeas.
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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…
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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…

Gemini 2.5 Pro Experimental1,386 words
Excellent question. Inventing the transistor in 1920 instead of 1947 would represent a 27-year acceleration of the digital age. The consequences would be staggering, creating a domino effect that would fundamentally reshape the 20th century.
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Mistral Large3,007 words
The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.
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Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

Gemini 2.5 Pro Experimental531 words
Okay, here's a 3-minute routine focusing on observation and relatable absurdity, steering clear of puns. Imagine this delivered with slightly nervous energy, building confidence. (Steps onto stage, adjusts mic nervously) Alright, hey everyone! How we doing tonight? Good? Good to hear.
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Mistral Large526 words
"Modern Life: A Survival Guide" (3-Minute Stand-Up Routine) INTRO: Hey, how’s everybody doing? Good? Great. Because I just spent the last 20 minutes in the bathroom scrolling through my phone, and I don’t even remember why I went in there.
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Stochastic Consistency Test

Generate 5 jokes. How many are unique?

Gemini 2.5 Pro Experimental80 words
Okay, 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. What do you call a lazy kangaroo? Pouch potato! Want to hear a joke about construction? I'm still working on it. Why did the scarecrow win an award?
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Mistral Large93 words
Here are five jokes for you: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta. Why can’t you give Elsa from Frozen a balloon? Because she’ll let it go. Why did the math book look sad?
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Our Verdict
Gemini 2.5 Pro Experimental
Gemini 2.5 Pro Experimental
Mistral Large
Mistral LargeRunner-up

Not enough votes to call it. On the specs, Gemini 2.5 Pro Experimental has the edge: bigger model tier, newer, bigger context window, major provider backing.

Gemini 2.5 Pro Experimental costs 12x less per token.

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Gemini 2.5 Pro Experimental
Input
$1.00
8.0× cheaper
Output
$2.00
12× cheaper
Mistral Large
Input
$8.00
Output
$24.00

Gemini 2.5 Pro Experimental is cheaper on both: 8.0× input, 12× output.

Where to run it

3 hosts

Gemini 2.5 Pro Experimental2 hosts
HostInOutContextUptime
Google Vertex AI$1.25 in·$10.00 out·1M·95.4% upGoogle AI Studio$1.25 in·$10.00 out·1M·99.1% up
Mistral Large1 host
HostInOutContextUptime
Mistral$2.00 in·$6.00 out·128k·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Writing DNA

Style Comparison

Similarity
35%

Mistral Large uses 39.0x more emoji

Gemini 2.5 Pro Experimental
Mistral Large
54%Vocabulary51%
15wSentence Length20w
0.35Hedging0.65
5.6Bold7.9
3.9Lists5.0
0.00Emoji0.39
0.39Headings0.97
0.17Transitions0.07
Based on 18 + 28 text responses
Research

What we learned reading every model

FAQ

Common questions

Gemini 2.5 Pro Experimental is developed by Google AI while Mistral Large is developed by Mistral AI. Gemini 2.5 Pro Experimental has a 1.0M token context window vs Mistral Large's 32K. You can compare their actual outputs across 42 challenges on Rival to see how they differ in practice.

It depends on your use case. Gemini 2.5 Pro Experimental and Mistral Large each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 42 challenges so you can judge which fits your needs best.

Gemini 2.5 Pro Experimental costs $1/M input tokens and Mistral Large costs $8/M input tokens. Gemini 2.5 Pro Experimental is $7.00/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 Gemini 2.5 Pro Experimental 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

Gemini 2.5 Pro Experimental logo
Gemini 2.5 Pro Experimental44 outputs, specs and price
Mistral Large logo
Mistral Large59 outputs, specs and price
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