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Real head-to-head · same prompt, one shot

Kimi K3 vs DeepSeek V4 Pro

Moonshot's 2.8T flagship — 1M context, tuned for long-horizon agent work. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.

Kimi K3 · context1M tokens
DeepSeek V4 Pro · context1M tokens
Kimi K3 · price$3 / M in
DeepSeek V4 Pro · priceAPI · pro tier
Kimi K3 · vendorMoonshot AI
DeepSeek V4 Pro · vendorDeepSeek

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 K3 and DeepSeek V4 Pro, side by side, on 50 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 K3 · Wired into the Agent OS as the `kimi-k3` Hermes profile and a K3 speed-toggle in the Kimi Code tab — used for long unattended agent runs where a slow-but-right model beats a fast-but-forgetful one.

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.

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 ↓
Kimi K3
DeepSeek V4 Pro
Game
Kimi K3 on Arcade
DeepSeek V4 Pro on Arcade
Game
Kimi K3 on Crypt
DeepSeek V4 Pro on Crypt
Game
Kimi K3 on Dogfight
DeepSeek V4 Pro on Dogfight
Game
Kimi K3 on Doom
DeepSeek V4 Pro on Doom
Kimi K3 on Dragonflight
DeepSeek V4 Pro on Dragonflight
🥉Kimi K3 on Dragonrealm
DeepSeek V4 Pro on Dragonrealm
Game
Kimi K3 on Flightsim
DeepSeek V4 Pro on Flightsim
Game
Kimi K3 on Game
DeepSeek V4 Pro on Game
Game
🥉Kimi K3 on Gtadrive
DeepSeek V4 Pro on Gtadrive
Game
🥉Kimi K3 on Gtafoot
DeepSeek V4 Pro on Gtafoot
Kimi K3 on Neonblaster
DeepSeek V4 Pro on Neonblaster
Game
🥈Kimi K3 on Neoncity
DeepSeek V4 Pro on Neoncity
Game
🥈Kimi K3 on Neonracer
DeepSeek V4 Pro on Neonracer
Kimi K3 on Nordiccrypt
DeepSeek V4 Pro on Nordiccrypt
Game
Kimi K3 on Outrun
DeepSeek V4 Pro on Outrun
Game
Kimi K3 on Parachute
DeepSeek V4 Pro on Parachute
Game
Kimi K3 on Pool
DeepSeek V4 Pro on Pool
Game
Kimi K3 on Racing
DeepSeek V4 Pro on Racing
Game
🥇Kimi K3 on Raycaster
DeepSeek V4 Pro on Raycaster
Game
Kimi K3 on Rpg
DeepSeek V4 Pro on Rpg
Game
Kimi K3 on Skyrim
DeepSeek V4 Pro on Skyrim
Kimi K3 on Twilightvale
DeepSeek V4 Pro on Twilightvale
Game
🥉Kimi K3 on Voxelcraft
DeepSeek V4 Pro on Voxelcraft
Other
🥈Kimi K3 on Matrixrain
DeepSeek V4 Pro on Matrixrain

Strengths & weaknesses I logged

Kimi K3

Strengths

  • Launch-day benchmarks put it around the Fable/Sol tier, with Terminal Bench (agentic terminal-driving) the standout
  • 1M-token context verified on this bench's needle test: exact recall from 162k tokens of noise in 18s
  • One-shot builds run long but land complete — its first bench game (13.4 min of thinking, 30,880 tokens) playtested with zero JS errors
  • Included in the Kimi coding plan — frontier tier without a new bill

Trade-offs

  • Slow on hard tasks — early testers report up to ~35 minutes at max reasoning; this bench saw 13+ minute single builds
  • Launch-day rate limits on OpenRouter (429s) — the coding-plan endpoint was the reliable route
  • Self-reports as K2.7 if you ask it — verify the served model via the API response, not the model's word

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

Pricing & context — the spec sheet

Spec Kimi K3 DeepSeek V4 Pro
VendorMoonshot AIDeepSeek
Context window1,048,576 tokens — a full codebase in working memory1,000,000-token context window
Price$3 / M inAPI · pro tier
Pricing detailLaunched July 16, 2026. 2.8T-param MoE (Moonshot's quickstart corrected the circulating 2.5T estimate). $3/M input on OpenRouter at launch; included at no extra cost in the Kimi coding plan (`k3` on the coding endpoint).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.
Release2026-07-162026-07
Bench coverage50/50 scored · avg 7.89/100/50 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 Kimi K3 and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — long-horizon agent runs → Kimi K3, checking whether deepseek's pro tier is worth the premium over flash 0731 → DeepSeek V4 Pro. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Kimi K3 vs DeepSeek V4 Pro

Which is better, Kimi K3 or DeepSeek V4 Pro?

On Goldie Bench, Kimi K3 averages no scored verdicts yet across the shared tasks, with 8 gold, 4 silver, 7 bronze overall. DeepSeek V4 Pro 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 Kimi K3 cost vs DeepSeek V4 Pro?

Kimi K3: Launched July 16, 2026. 2.8T-param MoE (Moonshot's quickstart corrected the circulating 2.5T estimate). $3/M input on OpenRouter at launch; included at no extra cost in the Kimi coding plan (`k3` on the coding endpoint). 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.

What's the context window for Kimi K3 vs DeepSeek V4 Pro?

Kimi K3 has a 1,048,576 tokens — a full codebase in working memory context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.

When should I pick Kimi K3 over DeepSeek V4 Pro?

Pick Kimi K3 for: long-horizon agent runs; whole-repo context work; terminal-driving agents. The trade-off is the weaknesses we logged on the bench: Slow on hard tasks — early testers report up to ~35 minutes at max reasoning; this bench saw 13+ minute single builds; Launch-day rate limits on OpenRouter (429s) — the coding-plan endpoint was the reliable route; Self-reports as K2.7 if you ask it — verify the served model via the API response, not the model's word.

When should I pick DeepSeek V4 Pro over Kimi K3?

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.

How does Goldie Bench score Kimi K3 vs DeepSeek V4 Pro?

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.

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.

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