Real head-to-head · same prompt, one shot

Qwen 3.7 vs N2 (Nex-N2-Pro)

Multilingual open-weights — strong on Chinese reasoning. vs Free local frontier model — runs in Hermes for $0.

Qwen 3.7 · context256K tokens
N2 (Nex-N2-Pro) · contextTBD
Qwen 3.7 · priceOpen weights · free for individuals
N2 (Nex-N2-Pro) · priceFree — runs locally inside Hermes
Qwen 3.7 · vendorAlibaba
N2 (Nex-N2-Pro) · vendorNex AGI

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Qwen 3.7 and N2 (Nex-N2-Pro), side by side, on 0 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

Qwen 3.7 · Wired alongside GLM-5.2 in Agent OS for open-weights agent loops where you want vendor diversity.

N2 (Nex-N2-Pro) · Wired into Hermes as the free local frontier coder. Dispatched from Agent OS for any task where the per-token bill would dominate.

Side-by-side on 5 shared tasks

Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).

Task ↓
Qwen 3.7
N2 (Nex-N2-Pro)
Game
🥈Qwen 3.7 on Arcade
— not attempted —
Page
Qwen 3.7 on Landing
— not attempted —
Sim
🥉
— not attempted —
Sim
🥉Qwen 3.7 on Orbit
— not attempted —
Visual
Qwen 3.7 on Voxel
— not attempted —

Strengths & weaknesses I logged

Qwen 3.7

Strengths

  • Open weights, free for individuals — same model class as GLM-5.2
  • Best-of-three on fluid simulation in the Goldie Bench bench
  • Multilingual depth — Chinese reasoning especially strong

Trade-offs

  • Only 5 tasks scored on the bench so far — small sample size
  • Trails GLM-5.2 on cinematic visual builds at similar pricing

N2 (Nex-N2-Pro)

Strengths

  • Vendor-reported 80.8% on SWE-bench Verified — top of the free open-weights field
  • Runs locally inside Hermes — no token meter, no rate limits
  • Builds two playable 3D games in one-shot per Julian's three-dragons writeup

Trade-offs

  • Vendor-reported benchmark (not independently verified yet)
  • No goldiebench per-task scores yet

Pricing & context — the spec sheet

Spec Qwen 3.7 N2 (Nex-N2-Pro)
VendorAlibabaNex AGI
Context window256,000 tokensSpecs not yet public
PriceOpen weights · free for individualsFree — runs locally inside Hermes
Pricing detailAlibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals.Nex AGI's flagship N2 (full name Nex-N2-Pro) runs free for individuals inside Hermes on your own Mac. Vendor-reported SWE-bench Verified: 80.8% — the highest published coding score among the free dragons (Kimi K2.6 / GLM / N2).
Release2026-062026-06-12
Bench coverage5/5 scored · avg 7.50/100/0 scored · avg —

The verdict — which should you pick?

Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Qwen 3.7 and N2 (Nex-N2-Pro) both into the Agent Operating System and dispatch each from the kanban by task type — open-weights alternative to glm-5.2 when you want a different model family → Qwen 3.7, local agent loops that need a free frontier-class coder → N2 (Nex-N2-Pro). That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Qwen 3.7 vs N2 (Nex-N2-Pro)

Which is better, Qwen 3.7 or N2 (Nex-N2-Pro)?

On Goldie Bench, Qwen 3.7 averages no scored verdicts yet across the shared tasks, with 0 gold, 1 silver, 2 bronze overall. N2 (Nex-N2-Pro) averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.

How much does Qwen 3.7 cost vs N2 (Nex-N2-Pro)?

Qwen 3.7: Alibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals. N2 (Nex-N2-Pro): Nex AGI's flagship N2 (full name Nex-N2-Pro) runs free for individuals inside Hermes on your own Mac. Vendor-reported SWE-bench Verified: 80.8% — the highest published coding score among the free dragons (Kimi K2.6 / GLM / N2).

What's the context window for Qwen 3.7 vs N2 (Nex-N2-Pro)?

Qwen 3.7 has a 256,000 tokens context window. N2 (Nex-N2-Pro) has a Specs not yet public context window.

When should I pick Qwen 3.7 over N2 (Nex-N2-Pro)?

Pick Qwen 3.7 for: Open-weights alternative to GLM-5.2 when you want a different model family; Multilingual workloads (Chinese, multi-script content); Fluid and particle simulations. The trade-off is the weaknesses we logged on the bench: Only 5 tasks scored on the bench so far — small sample size; Trails GLM-5.2 on cinematic visual builds at similar pricing.

When should I pick N2 (Nex-N2-Pro) over Qwen 3.7?

Pick N2 (Nex-N2-Pro) for: Local agent loops that need a free frontier-class coder; Privacy-sensitive workflows (no cloud round-trip); Operators experimenting with Hermes who want to compare local models against the cloud field. The trade-off is the weaknesses we logged on the bench: Vendor-reported benchmark (not independently verified yet); No goldiebench per-task scores yet.

How does Goldie Bench score Qwen 3.7 vs N2 (Nex-N2-Pro)?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

The same stack Julian uses

Run this stack yourself.

Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.

3,600+founders
258documented wins
38countries
$100k+/mocommunity MRR