Grok 4.7 vs Qwen 3.7

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 Grok 4.7 and Qwen 3.7, 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.

Grok 4.7 · Wired into the Agent OS Grok Build tab (4.7 / 4.6 / 4.5 picker, OpenRouter fallback when the CLI is signed out) and benched on twenty skill-infused game builds, each played through its full gameplay arc on a Metal GPU before the vision judge scored the played frame.

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

Where Grok 4.7 beat Qwen 3.7

The tasks where I gave Grok 4.7 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Qwen 3.7 beat Grok 4.7

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.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 20 scored shared tasks, the averages are essentially tied — Grok 4.7 7.15 vs Qwen 3.7 7.08. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.

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 Grok 4.7 and Qwen 3.7 both into the Agent Operating System and dispatch each from the kanban by task type — one-shot arcade, driving and shooter builds where the whole game has to arrive in a single file → Grok 4.7, open-weights alternative to glm-5.2 when you want a different model family → Qwen 3.7. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Grok 4.7 vs Qwen 3.7

Which is better, Grok 4.7 or Qwen 3.7?

On Goldie Bench, Grok 4.7 averages 7.15/10 across the shared tasks, with 0 gold, 2 silver, 3 bronze overall. Qwen 3.7 averages 7.08/10, with 0 gold, 0 silver, 0 bronze. Grok 4.7 wins the head-to-head 12–8.

How much does Grok 4.7 cost vs Qwen 3.7?

Grok 4.7: xAI's September 2026 release, priced exactly like Grok 4.6: $2 per million input tokens and $6 per million output on the standard tier, $4 / $12 on the Fast tier (double the output speed). OpenRouter lists the same model at $1.60 / $4.80. Qwen 3.7: Alibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals.

What's the context window for Grok 4.7 vs Qwen 3.7?

Grok 4.7 has a 500,000 tokens context window. Qwen 3.7 has a 256,000 tokens context window.

When should I pick Grok 4.7 over Qwen 3.7?

Pick Grok 4.7 for: One-shot arcade, driving and shooter builds where the whole game has to arrive in a single file; High-volume agent work priced at half what the other frontier models charge; Grok Build inside the Agent OS: pick 4.7 in the tab and everything it writes lands in the workspace. The trade-off is the weaknesses we logged on the bench: 2 of 20 builds died on load or never moved when played — crypt: hud is not a function; voxelcraft: mesh.computeBoundingSphere is not a function file:///Users/j; Independent Artificial Analysis Intelligence Index v4.3.2 puts it at 46, seven points behind Claude Fable 5.1 and GPT-6 at 53; Terminal-Bench 4.0 is the weak spot xAI reports itself: 38.0% at launch.

When should I pick Qwen 3.7 over Grok 4.7?

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.

How does Goldie Bench score Grok 4.7 vs Qwen 3.7?

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: Grok 4.7 · Qwen 3.7 · back to the leaderboard