Qwen 3.7 vs Grok 4.6

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 Grok 4.6, side by side, on 20 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.

Grok 4.6 · Benched on 16 skill-infused game builds, every one played through its full gameplay arc before scoring, then the broken ones were handed back to Grok 4.6 to repair itself.

Where Qwen 3.7 beat Grok 4.6

The tasks where I gave Qwen 3.7 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Grok 4.6 beat Qwen 3.7

The tasks where I gave Grok 4.6 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 20 scored shared tasks, Qwen 3.7 averaged 7.08/10, beating Grok 4.6's 5.95/10 by 1.12 points. Pick Qwen 3.7 when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.

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 Grok 4.6 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, high-volume agent work where the per-token bill decides what you can afford to run → Grok 4.6. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Qwen 3.7 vs Grok 4.6

Which is better, Qwen 3.7 or Grok 4.6?

On Goldie Bench, Qwen 3.7 averages 7.08/10 across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Grok 4.6 averages 5.95/10, with 1 gold, 0 silver, 0 bronze. Qwen 3.7 wins the head-to-head 13–6.

How much does Qwen 3.7 cost vs Grok 4.6?

Qwen 3.7: Alibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals. Grok 4.6: xAI's August 2026 flagship. $2 per million input tokens and $6 per million output tokens on the standard tier (the Fast tier is double), which is roughly half what the other frontier models charge for the same Artificial Analysis Intelligence Index score of 61.

What's the context window for Qwen 3.7 vs Grok 4.6?

Qwen 3.7 has a 256,000 tokens context window. Grok 4.6 has a 500,000 tokens context window.

When should I pick Qwen 3.7 over Grok 4.6?

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 Grok 4.6 over Qwen 3.7?

Pick Grok 4.6 for: High-volume agent work where the per-token bill decides what you can afford to run; Arcade, shooter and driving builds in one shot; Self-repair loops - it is unusually good at fixing a build when you hand it the real error. The trade-off is the weaknesses we logged on the bench: Flight models are its weak spot: both the flight sim and the dogfight shipped unflyable on the first pass; Two of sixteen game builds died on a hard error (a duplicate identifier and a bad computeBoundingSphere call); Worlds are lit and composed but usually untextured, so terrain reads as flat coloured planes.

How does Goldie Bench score Qwen 3.7 vs Grok 4.6?

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.

Related comparisons

Other head-to-heads using the same scoring system:

Full model pages: Qwen 3.7 · Grok 4.6 · back to the leaderboard