I Tested 4 AI Models: Free Nexand 2 Beat $25 Claude

For years, the rule was simple: the best AI was the most expensive AI. Claude Opus, Anthropic’s flagship model, charges approximately $25 per million output tokens. Then everything changed. A new model called Nexand 2 emerged from China—completely open source, completely free to download, and free to use commercially. Even more shocking, it scored above 80 on LiveBench, a real coding benchmark where GPT and Claude sit. I had to see if “free” meant “terrible.” So I put four models head-to-head: Kimi K2.7, GLM 5.1, Claude Opus 4, and Nexand 2 Pro. Same prompts, same tasks, same scrutiny. Here’s exactly what happened.

Key Takeaways

• Nexand 2 is genuinely free—input and output tokens cost $0, even for commercial use, yet it outperformed paid models on the game-building task.
• Claude Opus costs ~$25/million output tokens versus Kimi K2.7 at ~$4, GLM 5.1 at ~$3.08, and Nexand 2 at $0.
• Claude finished fastest on most tasks, but speed didn’t always equal the best final output.
• Kimi K2.7 failed completely on the game task—writing files but producing no playable output.
• GLM 5.1 took 25 minutes to build a game with movement bugs, making it impractical for rapid iteration.
• Operator’s Fusion mode can auto-switch between models mid-task, potentially optimizing for cost and quality dynamically.

The Cost Reality: Why This Comparison Matters

Before testing quality, I stared at the pricing table for a long time. Claude Opus charges roughly $5 per million input tokens and $25 per million output tokens. Kimi K2.7 drops that to about $0.75 input and $3.50 output. GLM 5.1 sits at approximately $0.98 input and $3.08 output. Then there’s Nexand 2: $0 for both input and output, with full commercial freedom.

I’ve been running AI-powered automation systems for my e-commerce operations for years. When you’re processing thousands of tokens daily, the difference between $25 and $0 isn’t theoretical—it’s the difference between a profitable workflow and one that bleeds money. But I refused to believe free could compete. That’s why I designed these tests.

Test 1: Building a Sales Funnel Website

I gave all four models the same prompt: build a website similar to my okenis.com system, a functional sales funnel with specific features. No hand-holding, no detailed specifications—just “make something like this.”

Kimi K2.7’s Attempt

Kimi produced a complete website quickly. It included cookie consent banners—something many developers forget—and structured the layout professionally. However, looking at the backend code, I spotted bugs. Text rendering had inconsistencies. The design felt obviously AI-generated, lacking the subtle refinements a human designer would add. Usable? Yes. Polished? Not quite.

Claude Opus’s Attempt

At nearly $25 per million tokens, Claude delivered the most visually refined result. The background graphics were superior, with animated highlights and a four-step automation showcase. Crucially, Claude didn’t invent random pricing—it pulled realistic figures, showing it understood context rather than hallucinating. The interactive elements worked smoothly. Between Kimi and Claude, Claude clearly produced the more professional output.

Nexand 2’s Attempt

Here’s where I got genuinely confused. The completely free model added background images to my simple prompt, created illuminated panels, and styled text in an “ultra-futuristic” aesthetic. It structured pricing packages and even built a forum section. Was it perfect? No—it worked from my prompt rather than researching live data from my site. But for $0? I kept asking myself: how is this possible?

GLM 5.1’s Attempt

GLM produced elegant opening animations and even added animated counters—a nice touch. However, it misspelled my brand name, adding incorrect characters. The backend implementation was decent but basic. With more prompt refinement, GLM could improve, but out of the box, it felt rougher than the others.

Test 2: Building a Minecraft-Style Game

Websites are one thing. Games test reasoning, physics, interactivity, and error handling. I gave all models the same prompt: build a Minecraft-like block game in a browser. Here’s where everything got strange.

Claude finished first. The game loaded, allowed left-click to break blocks, right-click to place them, and jump with upward movement. Was it perfect Minecraft? Honestly, I’ve never played Minecraft—my son tells me about it—but the mechanics seemed functional. I couldn’t definitively call it good or bad without player expertise.

Kimi K2.7 failed entirely. It wrote some code files but produced no playable game. The output files were essentially empty. I have no idea why—it simply didn’t execute the task.

Fusion mode disappointed. I expected great things since Fusion automatically switches to the best model for each subtask. Instead, the output was extremely blurry, almost unplayable. The colors were there, interaction was technically possible, but the visual quality made it practically useless.

Nexand 2 won decisively. After approximately 13 minutes, the free model delivered a functional block-building game. I could place boxes, break them, and navigate the environment. The visual clarity surpassed Fusion’s blurry mess. I sat there genuinely baffled: the $0 model outperformed the $25 one on a complex creative task.

For comparison, I also tested Minimax (which had previously built my best game). It produced something poetic and visually striking—almost too bright—but functional. When you fell off the world, the game ended. Different aesthetic, competent execution.

GLM 5.1 took 25 minutes and delivered a visually impressive but broken game. The character wouldn’t move properly. After that wait, the bugs made it unusable.

What About Speed and Smart Adaptation?

Nexand 2 has an intelligent side I appreciated: it adapts depth based on task complexity. Simple queries get fast answers; complex problems trigger deeper reasoning. Kimi K2.7 uses approximately 30% fewer reasoning steps than its predecessor, making it noticeably quicker. Claude remains methodical, step-by-step, never rushing.

But here’s what changed my thinking: Operator’s Fusion mode. This feature lets the system automatically switch between models during a task. If one model handles a subtask faster or better, Fusion routes to it, then returns to the primary model. For Cursor users, this infrastructure already exists. The implication is huge—you no longer need to manually choose “which AI is best.” The system optimizes in real-time, potentially combining Claude’s refinement with Nexand’s cost advantage.

My Honest Verdict: Which Model for Which Situation

After these tests, my recommendations split by use case:

For zero-budget, open-source coding: Nexand 2 is now my top recommendation. The game test proved it handles complex logic. One caveat: because it’s powerful, it demands strong hardware if you’re running it locally. Use Operator’s free cloud tier instead if your machine struggles.

For cheap, fast, open-source work: Kimi K2.7 at ~$4 per million tokens offers solid value. It failed the game test but performed adequately on websites. For routine coding tasks where speed matters, it’s worth considering.

For mission-critical, high-stakes code: Claude Opus remains the premium choice. When client work, security, or complex architecture demands the highest reliability, I still reach for Claude. But I pay accordingly—and increasingly question whether that premium is always justified.

For GLM 5.1: I can’t currently recommend it. Twenty-five minutes for a broken game, slower than competitors at similar pricing tiers. Perhaps future updates will improve it.

FAQ

Is Nexand 2 really completely free for commercial use?

Yes. Based on my testing through Operator, both input and output tokens are currently priced at $0, with explicit commercial usage rights. You can also download the open-source weights and run them locally.

How did Nexand 2 score on official coding benchmarks?

According to LiveBench data, Nexand 2 scored above 80 on coding tests, placing it in the same tier as GPT and Claude on that specific benchmark.

What hardware do I need to run Nexand 2 locally?

Nexand 2 is a powerful model requiring substantial GPU resources for local deployment. If you lack high-end hardware, using it through cloud platforms like Operator’s free tier is the practical alternative.

What is Fusion mode and should I use it?

Fusion mode automatically switches between AI models during a task, routing subtasks to whichever model handles them best or cheapest. In my game test, it underperformed individual models, but the concept is promising as the technology matures.

Conclusion

This test destroyed my assumption that price equals quality. Nexand 2, at literally zero cost, built the best game and a competent website. Claude still leads on polish and reliability, but the gap is narrowing faster than I expected. For my own operations, I’m now running hybrid setups—Claude for client-critical work, Nexand 2 for internal prototyping and experimentation. The real winner might be Fusion-style systems that combine them intelligently. If you’re still paying premium prices without testing alternatives, you’re potentially burning money. I run these comparisons weekly, and the landscape shifts constantly. The model that’s best today may be second-tier next month. Stay testing, stay skeptical, and never assume the expensive option is the right one.

Watch the full video (in Turkish — English subtitles available):

Tools & Community

• TurkoLister — the AI listing tool I use to turn Amazon products into optimized eBay UK listings in about 60 seconds (from £4.99/month, £1 one-week trial).
• AI & E-commerce Community — my Turkish-speaking community ($19/month) with weekly live sessions.
• Subscribe on YouTube — new experiments every week.