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  5. Llama 3.1 70B (Instruct)vsMiMo-V2.6-Pro
Updated Sep 2026

Llama 3.1 70B (Instruct)vsMiMo-V2.6-Pro

MiMo-V2.6-Pro is cheaper than Llama 3.1 70B (Instruct) at $0.435/M vs $0.59/M input tokens.

Llama 3.1 70B (Instruct) and MiMo-V2.6-Pro compared across 9 shared prompts
SpecLlama 3.1 70B (Instruct)MiMo-V2.6-Pro
Input price$0.59/M tokens$0.435/M tokens
Output price$0.79/M tokens$0.87/M tokens
Context window128K tokens1.0M tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedJul 2024Sep 2026
Side by side

Same prompt, both answers

Opening lines from 4 of the 9 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…

Llama 3.1 70B (Instruct)311 words
Here is a simple recipe for a delicious dish using only 7 common pantry ingredients: Dish Name: "Sunset Crunch Bites" Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup chopped peanuts 1/2 teaspoon salt 1/4 teaspoon cinnamon 1/4 cup chocolate chips (semi-sweet) Instructions: Preheat your oven to…
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MiMo-V2.6-Pro332 words
🍝 Moonlight Garlic Kiss Pasta A silky, garlicky butter pasta that proves simple ingredients can make something truly unforgettable. 7 Pantry Ingredients # Ingredient Amount 1 Spaghetti (or any pasta) 8 oz (half a standard box) 2 Butter 4 tablespoons 3 Garlic cloves 5 cloves, thinly sliced 4 Parmesan cheese ½ cup…
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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…

Llama 3.1 70B (Instruct)729 words
For the experienced software engineer: You're likely familiar with the concept of prediction in distributed systems, where a model predicts the likelihood of a certain event or outcome. Large language models like GPT or Claude take this concept to the next level by predicting the next word in a sequence of text.
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MiMo-V2.6-Pro1,338 words
Explaining Large Language Models to Three Audiences For the Software Engineer Think of an LLM as the most lossy, most brilliant compression algorithm ever built — except it's not compressing a specific file, it's compressing the patterns of human language into a fixed set of ~1 trillion floating-point parameters.
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Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

Llama 3.1 70B (Instruct)420 words
Here's a simple, actionable 1-month plan for someone starting their journey towards better health and longevity, focusing on 3 key areas: diet, exercise, and sleep. Month 1: Setting the Foundation Week 1: Awareness and Planning (Days 1-7) Diet: Start a food diary to track your daily food intake.
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MiMo-V2.6-Pro679 words
🌱 Your 1-Month Health & Longevity Starter Plan The 3 Pillars: Move · Nourish · Recover 🏃 MOVE (Exercise) Goal: Build a consistent, sustainable movement habit. Week 1 — Just Show Up Walk for 20 minutes daily (after lunch or dinner works great).
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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.…

Llama 3.1 70B (Instruct)419 words
Based on the pitch deck, I've identified the three weakest claims and provided suggestions for improvement: Weak Claim 1: "94% accuracy" (Slide 3) This claim is weak because it lacks context and credibility.
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MiMo-V2.6-Pro1,037 words
The 3 Weakest Claims in the MindMeld AI Pitch 🔴 "94% accuracy" non-invasive EEG decoding into text — (Slide 3) Why it's weak This is the claim the entire company rests on, and it directly contradicts the published state of the art.
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Our Verdict
Llama 3.1 70B (Instruct)
Llama 3.1 70B (Instruct)
MiMo-V2.6-Pro
MiMo-V2.6-Pro

Not enough votes to call it. On the specs, nothing separates them.

Too close to call
API pricing

Cost per 1M tokens

Llama 3.1 70B (Instruct)
Input
$0.59
Output
$0.79
1.1× cheaper
MiMo-V2.6-Pro
Input
$0.43
1.4× cheaper
Output
$0.87

MiMo-V2.6-Pro wins input (1.4× cheaper)·Llama 3.1 70B (Instruct) wins output (1.1× cheaper)

Where to run it

4 hosts, cheapest first

Llama 3.1 70B (Instruct)2 hosts
HostInOutContextUptime
DDeepInfrafp8$0.40 in·$0.40 out·131k·96.7% upAmazon Bedrock$0.72 in·$0.72 out·131k·100% up
MiMo-V2.6-Pro2 hosts
HostInOutContextUptime
DDeepInfrafp8$0.43 in·$0.87 out·1M·99.2% upXiaomifp8$0.43 in·$0.87 out·1M·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Llama 3.1 70B (Instruct) is developed by Meta AI while MiMo-V2.6-Pro is developed by Xiaomi. Llama 3.1 70B (Instruct) has a 128K token context window vs MiMo-V2.6-Pro's 1.0M. You can compare their actual outputs across 9 challenges on Rival to see how they differ in practice.

It depends on your use case. Llama 3.1 70B (Instruct) and MiMo-V2.6-Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 9 challenges so you can judge which fits your needs best.

Llama 3.1 70B (Instruct) costs $0.59/M input tokens and MiMo-V2.6-Pro costs $0.435/M input tokens. MiMo-V2.6-Pro is $0.15/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 Llama 3.1 70B (Instruct) and MiMo-V2.6-Pro 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

Llama 3.1 70B (Instruct) logo
Llama 3.1 70B (Instruct)56 outputs, specs and price
MiMo-V2.6-Pro logo
MiMo-V2.6-Pro9 outputs, specs and price
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