
Grok 4.7 vs Kimi K2.7 · No-Think
Grok 4.6's price, a bigger base model, and it builds games that hold together. vs Pure execution mode — no chain of thought.
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 Kimi K2.7 · No-Think, 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.
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.
Kimi K2.7 · No-Think · Reserved for templated transforms where the plan is already in the prompt — the model just executes.
Side-by-side on 47 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 = 🥉).
Strengths & weaknesses I logged
Grok 4.7
Strengths
- Averaged 6.86/10 on the same twenty skill-infused game briefs where Grok 4.6 averaged 5.63, winning 8 of the 11 head-to-heads
- Best one-shots on this run: arcade (8.6), dragonrealm (8.6), flightsim (8.5), every one played on a real GPU before scoring
- Longer reinforcement learning shows: it holds a 40-50KB single-file spec and wires the controls it advertises
- xAI's own coding numbers moved: CursorBench 4.0 46.3% (from 40.4%) and DeepSWE v1.1 71.0% (from 65.2%)
Trade-offs
- 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
Kimi K2.7 · No-Think
Strengths
- Skips planning to ship straight to code
- Useful when you've already done the reasoning in the prompt
- Predictable latency for batched jobs
Trade-offs
- Loses ground on multi-step tasks that benefit from planning
- Not scored on the standalone bench — see methodology
Pricing & context — the spec sheet
| Spec | Grok 4.7 | Kimi K2.7 · No-Think |
|---|---|---|
| Vendor | xAI | Moonshot AI |
| Context window | 500,000 tokens | 256,000 tokens |
| Price | $2 in / $6 out per M tokens | Flat plan (no per-token bill) |
| Pricing detail | 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. | Same flat-rate plan as standard Kimi K2.7 — No-Think disables the chain-of-thought layer at runtime. Vendor: Moonshot AI (moonshot.ai). |
| Release | 2026-09 | 2026-06 |
| Bench coverage | 11/11 scored · avg 6.86/10 | 0/47 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 Grok 4.7 and Kimi K2.7 · No-Think 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, templated transforms where the plan is in the prompt → Kimi K2.7 · No-Think. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Grok 4.7 vs Kimi K2.7 · No-Think
Which is better, Grok 4.7 or Kimi K2.7 · No-Think?
On Goldie Bench, Grok 4.7 averages no scored verdicts yet across the shared tasks, with 0 gold, 1 silver, 2 bronze overall. Kimi K2.7 · No-Think 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 Grok 4.7 cost vs Kimi K2.7 · No-Think?
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. Kimi K2.7 · No-Think: Same flat-rate plan as standard Kimi K2.7 — No-Think disables the chain-of-thought layer at runtime. Vendor: Moonshot AI (moonshot.ai).
What's the context window for Grok 4.7 vs Kimi K2.7 · No-Think?
Grok 4.7 has a 500,000 tokens context window. Kimi K2.7 · No-Think has a 256,000 tokens context window.
When should I pick Grok 4.7 over Kimi K2.7 · No-Think?
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 Kimi K2.7 · No-Think over Grok 4.7?
Pick Kimi K2.7 · No-Think for: Templated transforms where the plan is in the prompt; Batched code generation jobs; Workflows where you want the model to stop second-guessing. The trade-off is the weaknesses we logged on the bench: Loses ground on multi-step tasks that benefit from planning; Not scored on the standalone bench — see methodology.
How does Goldie Bench score Grok 4.7 vs Kimi K2.7 · No-Think?
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:
Grok 4.7 vs Fusion Kimi K2.7 · No-Think vs Fusion Grok 4.7 vs Claude Opus 5 Kimi K2.7 · No-Think vs Claude Opus 5 Grok 4.7 vs Hermes MoA Kimi K2.7 · No-Think vs Hermes MoA Grok 4.7 vs GPT-5.6 Sol Kimi K2.7 · No-Think vs GPT-5.6 SolFull model pages: Grok 4.7 · Kimi K2.7 · No-Think · back to the leaderboard
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 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.

































