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

Gemini 3.6 Flash vs DeepSeek V4 Pro

Google's launch-day Flash — faster, cheaper, fewer tokens. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.

Gemini 3.6 Flash · context1M tokens
DeepSeek V4 Pro · context1M tokens
Gemini 3.6 Flash · price$1.50 / M input
DeepSeek V4 Pro · priceAPI · pro tier
Gemini 3.6 Flash · vendorGoogle
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 Gemini 3.6 Flash 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.

Gemini 3.6 Flash · Benched via the native Gemini API on launch day. Game tasks use the skill-infused threejs-game-director prompt (same as the rest of the field) and are judged on a real mid-play frame by the same Opus vision judge.

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 ↓
Gemini 3.6 Flash
DeepSeek V4 Pro
Game
Gemini 3.6 Flash on Arcade
DeepSeek V4 Pro on Arcade
Game
Gemini 3.6 Flash on Crypt
DeepSeek V4 Pro on Crypt
Game
Gemini 3.6 Flash on Dogfight
DeepSeek V4 Pro on Dogfight
Game
Gemini 3.6 Flash on Doom
DeepSeek V4 Pro on Doom
Gemini 3.6 Flash on Dragonflight
DeepSeek V4 Pro on Dragonflight
Gemini 3.6 Flash on Dragonrealm
DeepSeek V4 Pro on Dragonrealm
Game
Gemini 3.6 Flash on Flightsim
DeepSeek V4 Pro on Flightsim
Game
Gemini 3.6 Flash on Game
DeepSeek V4 Pro on Game
Game
Gemini 3.6 Flash on Gtadrive
DeepSeek V4 Pro on Gtadrive
Game
Gemini 3.6 Flash on Gtafoot
DeepSeek V4 Pro on Gtafoot
Gemini 3.6 Flash on Neonblaster
DeepSeek V4 Pro on Neonblaster
Game
Gemini 3.6 Flash on Neoncity
DeepSeek V4 Pro on Neoncity
Game
Gemini 3.6 Flash on Neonracer
DeepSeek V4 Pro on Neonracer
Gemini 3.6 Flash on Nordiccrypt
DeepSeek V4 Pro on Nordiccrypt
Game
Gemini 3.6 Flash on Outrun
DeepSeek V4 Pro on Outrun
Game
Gemini 3.6 Flash on Parachute
DeepSeek V4 Pro on Parachute
Game
Gemini 3.6 Flash on Pool
DeepSeek V4 Pro on Pool
Game
Gemini 3.6 Flash on Racing
DeepSeek V4 Pro on Racing
Game
Gemini 3.6 Flash on Raycaster
DeepSeek V4 Pro on Raycaster
Game
Gemini 3.6 Flash on Rpg
DeepSeek V4 Pro on Rpg
Game
Gemini 3.6 Flash on Skyrim
DeepSeek V4 Pro on Skyrim
Gemini 3.6 Flash on Twilightvale
DeepSeek V4 Pro on Twilightvale
Game
Gemini 3.6 Flash on Voxelcraft
DeepSeek V4 Pro on Voxelcraft
Other
Gemini 3.6 Flash on Matrixrain
DeepSeek V4 Pro on Matrixrain

Strengths & weaknesses I logged

Gemini 3.6 Flash

Strengths

  • Fast one-shot builds — full skill-spec 3D games in ~60-120s of generation
  • Cheapest frontier-tier entry on the bench at $1.50/M input
  • 17% fewer output tokens than 3.5 Flash on the same workflows (Google's launch claim)

Trade-offs

  • Benched on launch day — partial run until the full 50-task batch completes
  • Flash tier, not a flagship — up against Pro/flagship-class models on this board

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 Gemini 3.6 Flash DeepSeek V4 Pro
VendorGoogleDeepSeek
Context window1,000,000-token context window1,000,000-token context window
Price$1.50 / M inputAPI · pro tier
Pricing detailLaunched 2026-07-21 alongside Gemini 3.5 Flash-Lite and 3.5 Flash Cyber. Google's pitch: higher intelligence than its predecessors on coding/ML/knowledge tasks while using 17% fewer output tokens, at a new lower price ($1.50 per million input tokens). Benched here via the native Gemini API on launch day.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.
Release2026-072026-07
Bench coverage50/50 scored · avg 7.08/100/50 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 Gemini 3.6 Flash and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — high-volume agentic work where token cost dominates → Gemini 3.6 Flash, 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 — Gemini 3.6 Flash vs DeepSeek V4 Pro

Which is better, Gemini 3.6 Flash or DeepSeek V4 Pro?

On Goldie Bench, Gemini 3.6 Flash averages no scored verdicts yet across the shared tasks, with 1 gold, 2 silver, 2 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 Gemini 3.6 Flash cost vs DeepSeek V4 Pro?

Gemini 3.6 Flash: Launched 2026-07-21 alongside Gemini 3.5 Flash-Lite and 3.5 Flash Cyber. Google's pitch: higher intelligence than its predecessors on coding/ML/knowledge tasks while using 17% fewer output tokens, at a new lower price ($1.50 per million input tokens). Benched here via the native Gemini API on launch day. 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 Gemini 3.6 Flash vs DeepSeek V4 Pro?

Gemini 3.6 Flash has a 1,000,000-token context window context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.

When should I pick Gemini 3.6 Flash over DeepSeek V4 Pro?

Pick Gemini 3.6 Flash for: High-volume agentic work where token cost dominates; Fast prototype builds you iterate on rather than one-shot masterpieces; Routing the everyday 90% while a flagship handles the hard 10%. The trade-off is the weaknesses we logged on the bench: Benched on launch day — partial run until the full 50-task batch completes; Flash tier, not a flagship — up against Pro/flagship-class models on this board.

When should I pick DeepSeek V4 Pro over Gemini 3.6 Flash?

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 Gemini 3.6 Flash 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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