Kimi K2.7 vs Grok 4.7

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 Kimi K2.7 and Grok 4.7, side by side, on 11 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.

Kimi K2.7 · Wired into the Agent OS as the heavy-lifter for game/sim prototypes and Kanban-dispatched code work. Mode toggled per task: Quality for one-shot games, Fast for short bursts.

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.

Where Kimi K2.7 beat Grok 4.7

The tasks where I gave Kimi K2.7 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Grok 4.7 beat Kimi K2.7

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.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 5 scored shared tasks, the averages are essentially tied — Kimi K2.7 8.20 vs Grok 4.7 7.90. 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 Kimi K2.7 and Grok 4.7 both into the Agent Operating System and dispatch each from the kanban by task type — interactive game prototypes you want shippable on the first prompt → Kimi K2.7, one-shot arcade, driving and shooter builds where the whole game has to arrive in a single file → Grok 4.7. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Kimi K2.7 vs Grok 4.7

Which is better, Kimi K2.7 or Grok 4.7?

On Goldie Bench, Kimi K2.7 averages 8.20/10 across the shared tasks, with 1 gold, 2 silver, 0 bronze overall. Grok 4.7 averages 7.90/10, with 0 gold, 1 silver, 2 bronze. Kimi K2.7 wins the head-to-head 3–2.

How much does Kimi K2.7 cost vs Grok 4.7?

Kimi K2.7: Available on Moonshot's flat-rate subscription plan — no per-token billing for individual builders. The plan covers all three speed modes (Fast, No-Think, Quality). Vendor: Moonshot AI (moonshot.ai), based in Beijing. 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.

What's the context window for Kimi K2.7 vs Grok 4.7?

Kimi K2.7 has a 256,000 tokens context window. Grok 4.7 has a 500,000 tokens context window.

When should I pick Kimi K2.7 over Grok 4.7?

Pick Kimi K2.7 for: Interactive game prototypes you want shippable on the first prompt; High-iteration agent loops where per-token cost would dominate; Long-context refactors using the 256K window inside Agent OS. The trade-off is the weaknesses we logged on the bench: Plays plainest on abstract visual prompts — synthwave grids, fluid sims, aurora — where GLM and Opus add more flair; Bronze average on the {{SITE_NAME}} bench despite the gold-medal games — its visual builds are accurate but understated.

When should I pick Grok 4.7 over Kimi K2.7?

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.

How does Goldie Bench score Kimi K2.7 vs Grok 4.7?

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: Kimi K2.7 · Grok 4.7 · back to the leaderboard