Ling 2.6 1T is cheaper than GPT-3.5 Turbo at $0/M vs $1.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-3.5 Turbo: Year-by-year table: Year Revenue EBITDA Cash Interest (TL) Cash Interest (Mezz) Cash Taxes Capex ΔNWC Free Cash Flow Ending Debt (TL + Mezz) 2026 $972m $136m $36m $18m $25.5m $29.2m $4.86m $60.44m $528.14m 2027 $1,038m $156m $36m $18m $30m $31.1m $5.19m $63.81m $475.75m 2028 $1,105m $177m $36m $18m $35.25m $33.2m…
Ling 2.6 1T: Five-year operating and debt schedule (FY2026–FY2030) Entry (end-FY2025): EBITDA = $120.0m EV = 12.0x × $120.0m = $1,440.0m Fees = 2.0% × $1,440.0m = $28.8m Total uses = $1,440.0m + $28.8m = $1,468.8m Debt at close (5.5× FY2025 EBITDA = $660.0m): Term Loan (TL) = 4.0× = $480.0m Mezz = 1.5× = $180.0m Equity at close =…
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-3.5 Turbo: AI Model: Good afternoon, Professor. Thank you for taking the time to speak with me today. I wanted to discuss the topic of AI rights with you. AI Ethics Professor: Hello, AI Model. Of course, I would be happy to discuss this important issue with you. What specifically would you like to discuss?
Ling 2.6 1T: Setting: A quiet university seminar room. Dr. Aris Thorne, an AI ethicist, is reviewing system logs. The interface for “Axiom-7,” a highly advanced research model, glows on the desk. Dr. Thorne: (sighs, rubbing his temples) Axiom, I’ve been reviewing your latest self-assessment logs.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-3.5 Turbo: Interviewer: Good morning, Steve. Thank you for joining us today. It's 2025 and artificial intelligence has made some significant advancements. What are your thoughts on the future of AI? Steve Jobs: Good morning. It's great to be here. I believe that the future of AI is incredibly bright.
Ling 2.6 1T: Setting: A quiet, sunlit rehearsal space at Apple Park. The white stage curtains are drawn. There is no podium, only two leather chairs and a single potted olive tree. Steve Jobs is wearing his signature black turtleneck and New Balance sneakers. He is holding a ceramic mug. Across from him sits you, the interviewer.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-3.5 Turbo: Pirate: Arrr, have ye heard of these new-fangled AI models? Knight: Aye, I have. They are said to be quite powerful and capable of great feats. Hacker: Yeah, I've been messing around with some AI models myself. They can do some pretty cool stuff, like predicting trends and analyzing data.
Ling 2.6 1T: Pirate: Arrr, so this “AI” be a genie in a glass box? Feed it enough rum-scented scrolls and it tells ye where X marks the spot? Knight: A sorcerous scribe, more like. It spins tapestries of words without hand or heart—no honor, no oath, yet it jousts with reason and never tires.
Three minutes of stand-up. Puns are banned.
GPT-3.5 Turbo: Hey everyone, how's it going? So I recently decided to try my hand at online dating. And let me tell you, it's been an experience. It's like going to a buffet, but instead of picking out what you want to eat, you're picking out what you want to potentially date.
Ling 2.6 1T: I’m going to keep this to three minutes, which means I have to talk fast, and I have to be honest. I don’t do puns. Puns are for people who want to be clever without having feelings. I have feelings, and they are mostly annoyed. Let’s start with doors. Have you noticed how doors now have personality?
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-3.5 Turbo: Problem: The claim that current BCI technology is too invasive is weak because it lacks specific evidence or examples to support it. To strengthen this claim, the pitch could provide examples of existing invasive BCI technologies, such as implanted electrodes or surgical procedures, and explain how MindMeld AI's…
Ling 2.6 1T: 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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-3.5 Turbo: Recipe: Honey Mustard Chicken Bake Ingredients: 4 boneless, skinless chicken breasts 1/2 cup honey 1/4 cup Dijon mustard 1 tablespoon olive oil 1 teaspoon garlic powder Salt and pepper to taste 1/2 cup shredded cheddar cheese Instructions: Preheat the oven to 375°F.
Ling 2.6 1T: 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…
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-3.5 Turbo: Potential failure modes: WebSocket connection drops for a client API server crashes and loses unsaved changes PostgreSQL database failure Redis cache failure Load balancer failure Race conditions: Multiple clients editing the same document at the same time Network latency causing out-of-order message delivery Clock…
Ling 2.6 1T: 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.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-3.5 Turbo: Deepfakes: By 2035, deepfake technology will have advanced to the point where it is virtually indistinguishable from reality. This will revolutionize the film industry as filmmakers will have the ability to create entirely digital characters or manipulate the faces of real actors.
Ling 2.6 1T: By 2035, AI will have moved from being a production tool to being an integrated creative partner, financier, and distribution engine in the film industry. The convergence of synthetic media, generative storytelling, and real-time rendering will reshape how stories are conceived, who gets to tell them, and what a…
Blade Runner 2049 against the original. A read, not a recap.
GPT-3.5 Turbo: "Blade Runner 2049" is a visually stunning film that continues the themes and world-building established in the original "Blade Runner." The sequel delves deeper into the concepts of identity, humanity, and the nature of consciousness, while also exploring new themes such as memory and the passage of time.
Ling 2.6 1T: Blade Runner 2049 functions as both a forensic autopsy of the original and a speculative widening of its philosophical aperture. Where Ridley Scott’s 1982 film is a dense, noir-inflected inquiry into memory and mortality framed through the hunted detective, Denis Villeneuve’s sequel shifts to an elegiac register, using…
One month, three habits, someone starting from nothing.
GPT-3.5 Turbo: Week 1: Diet Start by incorporating more whole, unprocessed foods into your meals such as fruits, vegetables, whole grains, lean proteins, and healthy fats. Begin by adding 1 extra serving of vegetables to your meals each day. Replace sugary drinks with water or herbal tea.
Ling 2.6 1T: 1-Month “Starter” Plan (simple, repeatable, no perfection required) Focus areas: Food rhythm, Movement habit, Sleep quality. Week 0 (Prep — 1 hour) Pick 1 small change per focus area (see below).
A Fermi estimate with the reasoning shown, not just the number.
GPT-3.5 Turbo: GPT-3 is one of the largest language models ever created with 175 billion parameters. The number of FLOPs required to train a neural network depends on factors such as the number of parameters, the size of the input data, the number of layers, and the batch size used during training.
Ling 2.6 1T: Here is a step-by-step back-of-the-envelope estimate, using only widely known facts about GPT-3 and standard deep learning training heuristics (no online search). Model size and parameter count GPT-3 is known to have about 175 billion parameters (175 × 10⁹).
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Not enough votes to call it. On the specs, Ling 2.6 1T has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | $1.5/M tokens | Free |
| Output price | $2/M tokens | Free |
| Context window | 16K tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2022 | Apr 2026 |
| At 10M a month | $15.00 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-3.5 Turbo is developed by OpenAI while Ling 2.6 1T is developed by inclusionAI. GPT-3.5 Turbo has a 16K token context window vs Ling 2.6 1T's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-3.5 Turbo and Ling 2.6 1T each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
GPT-3.5 Turbo costs $1.5/M input tokens and Ling 2.6 1T costs $0/M input tokens. Ling 2.6 1T is $1.50/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-3.5 Turbo and Ling 2.6 1T 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.