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. Ling 2.6 1TvsQwen3.8 Max Prime
Updated Sep 2026

Ling 2.6 1TvsQwen3.8 Max Prime

Ling 2.6 1T is cheaper than Qwen3.8 Max Prime at $0/M vs $4/M input tokens.

Ling 2.6 1T and Qwen3.8 Max Prime compared across 19 shared prompts
SpecLing 2.6 1TQwen3.8 Max Prime
Input priceFree$4/M tokens
Output priceFree$12/M tokens
Context window262K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedApr 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…

Ling 2.6 1T151 words
Dish name: Pantry 7 Crunch Bowls Ingredients Pasta or rice (about 2 cups cooked) Canned black beans (1 can, rinsed) Canned diced tomatoes (1 can) Peanut butter (3–4 Tbsp) Soy sauce or tamari (2 Tbsp) Honey or maple syrup (1 Tbsp) Any spice/herb you keep (chili flakes, cumin, or garlic powder — about 1 tsp) Instructions…
Read the full answer
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

Debug This Architecture

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

Ling 2.6 1T1,438 words
Below is a failure-mode, race-condition and bottleneck audit of the proposed real-time collaborative editor, followed by specific fixes with explicit trade-offs. I have grouped issues by layer so you can prioritize remediation.
Read the full answer
Qwen3.8 Max Prime2,271 words
Architecture Analysis: Failure Modes, Race Conditions & Scaling Bottlenecks SYNC & CONSISTENCY LAYER 1.1 Last-Write-Wins with Client Clocks (Critical) Failure Mode: Client clocks are unreliable. A user with a clock skewed +5 minutes will always "win" conflicts.
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.…

Ling 2.6 1T853 words
Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, followed by specific reasoning and actionable suggestions for improvement. Weakness 1: The Solution (Slide 3) The Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy.
Read the full answer
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.
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…

Ling 2.6 1T1,025 words
1. Experienced software engineer (distributed systems / APIs, skeptical of “next-word prediction”) Think of training not as programming logic but as compiling a usage graph across an entire dependency tree of human intent.
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.
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…

Ling 2.6 1T1,399 words
Assumptions to make the counterfactual coherent The “transistor” invented in 1920 is a crude, low-frequency point-contact device that can switch and amplify, but is expensive, unreliable, and not yet manufacturable at scale.
Read the full answer
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.
Read the full answer

Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

Ling 2.6 1T932 words
INTERNAL INVESTMENT COMMITTEE MEMO Subject: LedgerLift (LLLT) – Long opportunity, quality SaaS at a discount Recommendation and price target Recommendation: Long 12-month price target: $62–$70 (27–33% upside from $46) Thesis (2 sentences): LedgerLift is a durable B2B spend-management and AP-automation platform with…
Read the full answer
Qwen3.8 Max Prime1,001 words
INVESTMENT COMMITTEE MEMO LedgerLift (LLLT) B2B Spend Management & AP Automation SaaS Date: [Current] Analyst: [Name] Sector: Enterprise Software RECOMMENDATION LONG 12-Month Price Target: $50–$58 Current: $46 Thesis: LedgerLift is a high-quality compounder (123% NRR, 18-month CAC payback, 92% subscription mix) trading…
Read the full answer
Our Verdict
Ling 2.6 1T
Ling 2.6 1T
Qwen3.8 Max Prime
Qwen3.8 Max Prime

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

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Ling 2.6 1T
Input
$0.000
Output
$0.000
Qwen3.8 Max Prime
Input
$4.00
Output
$12.00
Where to run it

1 host

Ling 2.6 1T

No hosts listed on OpenRouter.

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

Ling 2.6 1T is developed by inclusionAI while Qwen3.8 Max Prime is developed by Qwen. Ling 2.6 1T 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. Ling 2.6 1T 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.

Ling 2.6 1T costs $0/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. Ling 2.6 1T is $4.00/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 Ling 2.6 1T 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.

Keep exploring

More comparisons

Against the newest arrivals

Ling 2.6 1T logoSolar Mini 4 logo
Ling 2.6 1T vs Solar Mini 4Landed Sep 2026
Qwen3.8 Max Prime logoGLM 5.3 Prime logo
Qwen3.8 Max Prime vs GLM 5.3 PrimeLanded Sep 2026
Ling 2.6 1T logoQwen3.8 Omni Flash logo
Ling 2.6 1T vs Qwen3.8 Omni FlashLanded Sep 2026
Qwen3.8 Max Prime logoCommand A+ logo
Qwen3.8 Max Prime vs Command A+Landed Sep 2026
Ling 2.6 1T logoClaude Opus 5.5 logo
Ling 2.6 1T vs Claude Opus 5.5Landed Sep 2026
Qwen3.8 Max Prime logoGPT-6 Luna Pro logo
Qwen3.8 Max Prime vs GPT-6 Luna ProLanded Sep 2026
Ling 2.6 1T logoGPT-6 Sol Pro logo
Ling 2.6 1T vs GPT-6 Sol ProLanded Sep 2026
Qwen3.8 Max Prime logoGPT-6 Luna logo
Qwen3.8 Max Prime vs GPT-6 LunaLanded Sep 2026

Same lab, same size, long tail

Ling 2.6 1T logoLing 3.0 Flash logo
Ling 2.6 1T vs Ling 3.0 FlashSame lab
Ling 2.6 1T logoLing 3.0 Flash Fin (free) logo
Ling 2.6 1T vs Ling 3.0 Flash Fin (free)Same lab
Qwen3.8 Max Prime logoQwen3.8 Omni Flash logo
Qwen3.8 Max Prime vs Qwen3.8 Omni FlashSame lab
Qwen3.8 Max Prime logoQwen3.7 Flash logo
Qwen3.8 Max Prime vs Qwen3.7 FlashSame lab
Ling 2.6 1T logoQwQ 32B logo
Ling 2.6 1T vs QwQ 32BCross-provider
Qwen3.8 Max Prime logoRing 2.6 1T logo
Qwen3.8 Max Prime vs Ring 2.6 1TCross-provider
Ling 2.6 1T logoSeed 2.0 Code logo
Ling 2.6 1T vs Seed 2.0 CodeNew provider
Ling 2.6 1T logoSeed 2.0 Lite logo
Ling 2.6 1T vs Seed 2.0 LiteNew provider

Model pages

Ling 2.6 1T logo
Ling 2.6 1T58 outputs, specs and price
Qwen3.8 Max Prime logo
Qwen3.8 Max Prime19 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