Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed
  1. Home
  2. /
  3. Compare
  4. /
  5. Nemotron 3 Nano Omni (free)vsQwen3.8 Max
Updated Aug 2026

Nemotron 3 Nano Omni (free)vsQwen3.8 Max

Nemotron 3 Nano Omni (free) is cheaper than Qwen3.8 Max at $0/M vs $2/M input tokens.

Nemotron 3 Nano Omni (free) and Qwen3.8 Max compared across 15 shared prompts
SpecNemotron 3 Nano Omni (free)Qwen3.8 Max
Input priceFree$2/M tokens
Output priceFree$6/M tokens
Context window256K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedApr 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 prompts both answered. Formatting stripped, words untouched.

Mini LBO Underwrite

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

Nemotron 3 Nano Omni (free)1,246 words
We need to build a simplified year-by-year table FY2026-FY2030. First, compute initial purchase price: EBITDA FY2025 = $120m. Purchase price = 12.0x EBITDA = 12 * 120 = $1,440m (enterprise value). Transaction fees = 2.0% of EV = 0.02 * 1440 = $28.8m, paid at close from equity. Total leverage at close = 5.5x EBITDA.
Read the full answer
Qwen3.8 Max828 words
Base-case underwriting (FY2026–FY2030) Assumptions / conventions used All amounts in $m unless noted. Close occurs at end of FY2025; FY2026 is Year 1. Interest is calculated on beginning-of-year debt balances; optional Term Loan paydown occurs at year-end. Term Loan amortization: 1.0% of original $480m TL = $4.8m/yr.
Read the full answer

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…

Nemotron 3 Nano Omni (free)326 words
Dish Name: Sunset Tomato‑Garlic Pasta Estimated Time: Prep 10 min   Cook 20 min   Total ≈ 30 min 7 Pantry Ingredients # Ingredient Quantity (serves 2) 1 Spaghetti (or any dried pasta) 200 g (≈ 7 oz) 2 Canned crushed tomatoes 1 cup (≈ 240 ml) 3 Garlic cloves 2 large, minced 4 Onion ½ medium, finely diced 5 Olive oil…
Read the full answer
Qwen3.8 Max132 words
Dish Name: Golden Hour Peanut Butter Oat Clusters Ingredients (7): 1 cup rolled oats ½ cup peanut butter ⅓ cup honey ½ cup chocolate chips 1 teaspoon vanilla extract ½ teaspoon ground cinnamon ¼ teaspoon salt Instructions: Optional but recommended: Toast the oats in a dry skillet over medium heat for 3–4 minutes…
Read the full answer

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Nemotron 3 Nano Omni (free)130 words
We need to list potential failure modes, race conditions, scaling bottlenecks, and propose specific solutions with trade-offs. Must be thorough. Consider WebSocket, load balancer, statelessness, DB writes, replication, polling, timestamp reliance, concurrency, partition tolerance, network partitions, server crashes…
Read the full answer
Qwen3.8 Max5,155 words
Below is a comprehensive failure-mode review of the proposed architecture. I will group related issues where the same root cause creates multiple symptoms. The biggest problems are: Client-clock last-write-wins is not safe for collaborative editing.
Read the full answer

Historical Counterfactual Analysis

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

Nemotron 3 Nano Omni (free)2,564 words
Premise – The point‑contact transistor is invented in 1920 (instead of 1947) and quickly becomes a reliable, reproducible solid‑state amplifier. By the mid‑1920s a handful of laboratories are already producing germanium‑based devices, and by the early 1930s a modest “transistor industry” exists, albeit with low yields…
Read the full answer
Qwen3.8 Max4,497 words
A useful way to think about this is not “1980 becomes 2007.” The transistor would accelerate electronics, but every technology has bottlenecks: materials chemistry, precision manufacturing, rockets, batteries, displays, institutional capacity, and war.
Read the full answer

Advanced Longevity Plan (Biohacker)

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

Nemotron 3 Nano Omni (free)3,140 words
3‑Month “Longevity‑Performance” Blueprint Target: Bio‑hacker (25‑45 y, healthy but wants to maximise lifespan, physical power, and cognitive sharpness). Duration: 12 weeks (≈3 months) – broken into three 4‑week phases. Core Principle: Measure → Optimize → Re‑measure.
Read the full answer
Qwen3.8 Max3,196 words
12-Week Biohacker Longevity & Performance Protocol Goal: improve metabolic health, strength, VO₂max proxies, sleep, HRV/stress resilience, cognitive output, and longevity-related biomarkers over 3 months. Medical disclaimer: This is an aggressive self-experimentation framework, not medical advice.
Read the full answer

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.…

Nemotron 3 Nano Omni (free)540 words
The three weakest claims in the deck – and why they don’t hold up under scrutiny # Claim (as written) Why it’s weak (evidence / logical gaps) How to make it credible (concrete improvements) 1 Vision – “We’re building the future of human‑AI collaboration.
Read the full answer
Qwen3.8 Max1,957 words
The 3 weakest claims are the pre-thought prediction claim, the 94% accuracy / any language / any device claim, and the $180B TAM claim. These are the ones most likely to undermine credibility with investors, technical reviewers, or enterprise buyers because they are either logically inconsistent, under-specified, or…
Read the full answer
Our Verdict
Qwen3.8 Max
Qwen3.8 Max
Nemotron 3 Nano Omni (free)
Nemotron 3 Nano Omni (free)Runner-up

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

Slight edge
API pricing

Cost per 1M tokens

Nemotron 3 Nano Omni (free)
Input
$0.000
Output
$0.000
Qwen3.8 Max
Input
$2.00
Output
$6.00
Where to run it

2 hosts

Nemotron 3 Nano Omni (free)1 host
HostInOutContextUptime
NVIDIAdegraded$0 in·$0 out·256k·77.6% up
Qwen3.8 Max1 host
HostInOutContextUptime
Alibaba Cloud$2.00 in·$6.00 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

Nemotron 3 Nano Omni (free) is developed by NVIDIA while Qwen3.8 Max is developed by Qwen. Nemotron 3 Nano Omni (free) has a 256K token context window vs Qwen3.8 Max's 1.0M. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. Nemotron 3 Nano Omni (free) and Qwen3.8 Max each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

Nemotron 3 Nano Omni (free) costs $0/M input tokens and Qwen3.8 Max costs $2/M input tokens. Nemotron 3 Nano Omni (free) is $2.00/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 Nemotron 3 Nano Omni (free) and Qwen3.8 Max 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.

Keep exploring

More comparisons

Against the newest arrivals

Nemotron 3 Nano Omni (free) logoDeepSeek V4 Flash Vision Exp logo
Nemotron 3 Nano Omni (free) vs DeepSeek V4 Flash Vision ExpLanded Sep 2026
Qwen3.8 Max logoSolar Pro 4 logo
Qwen3.8 Max vs Solar Pro 4Landed Sep 2026
Nemotron 3 Nano Omni (free) logoHy3 logo
Nemotron 3 Nano Omni (free) vs Hy3Landed Sep 2026
Qwen3.8 Max logoQwen3.7 Flash logo
Qwen3.8 Max vs Qwen3.7 FlashLanded Sep 2026
Nemotron 3 Nano Omni (free) logoLing 3.0 Flash logo
Nemotron 3 Nano Omni (free) vs Ling 3.0 FlashLanded Sep 2026
Qwen3.8 Max logoMuse Glimmer 30B logo
Qwen3.8 Max vs Muse Glimmer 30BLanded Sep 2026
Nemotron 3 Nano Omni (free) logoGLM 5.3 logo
Nemotron 3 Nano Omni (free) vs GLM 5.3Landed Sep 2026
Qwen3.8 Max logoTernary Bonsai 2 27B logo
Qwen3.8 Max vs Ternary Bonsai 2 27BLanded Sep 2026

Same lab, same size, long tail

Nemotron 3 Nano Omni (free) logoNemotron 3.5 Lightning logo
Nemotron 3 Nano Omni (free) vs Nemotron 3.5 LightningSame lab
Nemotron 3 Nano Omni (free) logoNemotron 3 Ultra logo
Nemotron 3 Nano Omni (free) vs Nemotron 3 UltraSame lab
Qwen3.8 Max logoQwen3.8 Flash logo
Qwen3.8 Max vs Qwen3.8 FlashSame lab
Qwen3.8 Max logoQwen3.8 Max (0902) logo
Qwen3.8 Max vs Qwen3.8 Max (0902)Same lab
Nemotron 3 Nano Omni (free) logoKimi K2.7 Code logo
Nemotron 3 Nano Omni (free) vs Kimi K2.7 CodeNew provider
Nemotron 3 Nano Omni (free) logoKimi K3 logo
Nemotron 3 Nano Omni (free) vs Kimi K3New provider
Nemotron 3 Nano Omni (free) logoKimi Linear 48B A3B Instruct logo
Nemotron 3 Nano Omni (free) vs Kimi Linear 48B A3B InstructNew provider
Nemotron 3 Nano Omni (free) logoLaguna S 2.1 (free) logo
Nemotron 3 Nano Omni (free) vs Laguna S 2.1 (free)Same size

Model pages

Nemotron 3 Nano Omni (free) logo
Nemotron 3 Nano Omni (free)17 outputs, specs and price
Qwen3.8 Max logo
Qwen3.8 Max22 outputs, specs and price
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed