
Real head-to-head · same prompt, one shot
DeepSeek V4 Pro vs Kimi K2.7 · Quality
DeepSeek's flagship tier — benched head-to-head against its own cheap Flash. vs Quality mode — deepest thinking, best output.
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 DeepSeek V4 Pro and Kimi K2.7 · Quality, side by side, on 47 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.
DeepSeek V4 Pro · Benched on all 50 GoldieBench tasks via api.deepseek.com with the same pipeline as the Flash 0731 run, then published as a live side-by-side: goldiebench.com/vs-live/deepseek-flash-vs-pro.html loads both builds of every task in twin panes.
Kimi K2.7 · Quality · Reserved for one-shot builds where the output is the deliverable — polish over speed.
Side-by-side on 50 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 ↓
DeepSeek V4 Pro
Kimi K2.7 · Quality
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Page
Strengths & weaknesses I logged
DeepSeek V4 Pro
Strengths
- Flagship reasoning tier on the same official API and 1M context as Flash
- Ran the identical 50-prompt set as V4 Flash 0731 — a clean same-vendor A/B
- Reasoning-first: thinks before writing every build
Trade-offs
- Unranked — builds are on the bench but not yet scored by the Opus vision judge
- Slower and pricier per build than Flash — the whole question is whether that buys quality
Kimi K2.7 · Quality
Strengths
- Highest-effort reasoning path of the three Kimi modes
- Hand-tuned output polish on creative tasks
- Same flat-rate plan as Fast and No-Think — no premium
Trade-offs
- Slower than Fast and No-Think — not for snappy loops
- Not scored on the standalone bench — see methodology
Pricing & context — the spec sheet
| Spec | DeepSeek V4 Pro | Kimi K2.7 · Quality |
|---|---|---|
| Vendor | DeepSeek | Moonshot AI |
| Context window | 1,000,000-token context window | 256,000 tokens |
| Price | API · pro tier | Flat plan (no per-token bill) |
| Pricing detail | DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim. | Same flat-rate plan as standard Kimi K2.7 — Quality mode runs the deepest reasoning path. Vendor: Moonshot AI (moonshot.ai). |
| Release | 2026-07 | 2026-06 |
| Bench coverage | 0/50 scored · avg — | 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 DeepSeek V4 Pro and Kimi K2.7 · Quality both into the Agent Operating System and dispatch each from the kanban by task type — checking whether deepseek's pro tier is worth the premium over flash 0731 → DeepSeek V4 Pro, one-shot games and sims where polish matters → Kimi K2.7 · Quality. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — DeepSeek V4 Pro vs Kimi K2.7 · Quality
Which is better, DeepSeek V4 Pro or Kimi K2.7 · Quality?
On Goldie Bench, DeepSeek V4 Pro averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 bronze overall. Kimi K2.7 · Quality 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 DeepSeek V4 Pro cost vs Kimi K2.7 · Quality?
DeepSeek V4 Pro: DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim. Kimi K2.7 · Quality: Same flat-rate plan as standard Kimi K2.7 — Quality mode runs the deepest reasoning path. Vendor: Moonshot AI (moonshot.ai).
What's the context window for DeepSeek V4 Pro vs Kimi K2.7 · Quality?
DeepSeek V4 Pro has a 1,000,000-token context window context window. Kimi K2.7 · Quality has a 256,000 tokens context window.
When should I pick DeepSeek V4 Pro over Kimi K2.7 · Quality?
Pick DeepSeek V4 Pro for: Checking whether DeepSeek's pro tier is worth the premium over Flash 0731; Hard single-shot builds where extra reasoning depth may pay off. The trade-off is the weaknesses we logged on the bench: Unranked — builds are on the bench but not yet scored by the Opus vision judge; Slower and pricier per build than Flash — the whole question is whether that buys quality.
When should I pick Kimi K2.7 · Quality over DeepSeek V4 Pro?
Pick Kimi K2.7 · Quality for: One-shot games and sims where polish matters; Creative writing where you want the model to slow down; Final-pass refinement of an earlier draft. The trade-off is the weaknesses we logged on the bench: Slower than Fast and No-Think — not for snappy loops; Not scored on the standalone bench — see methodology.
How does Goldie Bench score DeepSeek V4 Pro vs Kimi K2.7 · Quality?
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:
DeepSeek V4 Pro vs Fusion Kimi K2.7 · Quality vs Fusion DeepSeek V4 Pro vs Claude Opus 5 Kimi K2.7 · Quality vs Claude Opus 5 DeepSeek V4 Pro vs Hermes MoA Kimi K2.7 · Quality vs Hermes MoA DeepSeek V4 Pro vs GPT-5.6 Sol Kimi K2.7 · Quality vs GPT-5.6 SolFull model pages: DeepSeek V4 Pro · Kimi K2.7 · Quality · back to the leaderboard
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 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.
4,000+founders
258documented wins
38countries
$59/momonthly














































