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

Opus 4.8 vs DeepSeek V4 Pro

The reasoning king — deepest thinking, premium price. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.

Opus 4.8 · context200K tokens
DeepSeek V4 Pro · context1M tokens
Opus 4.8 · price$15 / $75 per M tokens
DeepSeek V4 Pro · priceAPI · pro tier
Opus 4.8 · vendorAnthropic
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 Opus 4.8 and DeepSeek V4 Pro, 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.

Opus 4.8 · The default when the build has to ship on the first prompt — Opus is the safety net inside Agent OS for hard one-shots.

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 ↓
Opus 4.8
DeepSeek V4 Pro
Game
🥉Opus 4.8 on Arcade
DeepSeek V4 Pro on Arcade
Game
Opus 4.8 on Crypt
DeepSeek V4 Pro on Crypt
Game
Opus 4.8 on Dogfight
DeepSeek V4 Pro on Dogfight
Game
🥈Opus 4.8 on Doom
DeepSeek V4 Pro on Doom
Opus 4.8 on Dragonflight
DeepSeek V4 Pro on Dragonflight
Opus 4.8 on Dragonrealm
DeepSeek V4 Pro on Dragonrealm
Game
Opus 4.8 on Flightsim
DeepSeek V4 Pro on Flightsim
Game
Opus 4.8 on Game
DeepSeek V4 Pro on Game
Game
Opus 4.8 on Gtadrive
DeepSeek V4 Pro on Gtadrive
Game
Opus 4.8 on Gtafoot
DeepSeek V4 Pro on Gtafoot
Opus 4.8 on Neonblaster
DeepSeek V4 Pro on Neonblaster
Game
Opus 4.8 on Neoncity
DeepSeek V4 Pro on Neoncity
Game
Opus 4.8 on Neonracer
DeepSeek V4 Pro on Neonracer
Opus 4.8 on Nordiccrypt
DeepSeek V4 Pro on Nordiccrypt
Game
Opus 4.8 on Outrun
DeepSeek V4 Pro on Outrun
Game
Opus 4.8 on Parachute
DeepSeek V4 Pro on Parachute
Game
Opus 4.8 on Pool
DeepSeek V4 Pro on Pool
Game
Opus 4.8 on Racing
DeepSeek V4 Pro on Racing
Game
Opus 4.8 on Raycaster
DeepSeek V4 Pro on Raycaster
Game
Opus 4.8 on Rpg
DeepSeek V4 Pro on Rpg
Game
Opus 4.8 on Skyrim
DeepSeek V4 Pro on Skyrim
Opus 4.8 on Twilightvale
DeepSeek V4 Pro on Twilightvale
Game
Opus 4.8 on Voxelcraft
DeepSeek V4 Pro on Voxelcraft
Page
Opus 4.8 on Aipbpromo
DeepSeek V4 Pro on Aipbpromo

Strengths & weaknesses I logged

Opus 4.8

Strengths

  • Most consistent across the Goldie Bench bench — no weak build, 8.46/10 average
  • Deepest one-shot reasoning, especially on game-feel and physics
  • Extended thinking mode handles up to 1M tokens of context

Trade-offs

  • 5–10× the per-token cost of every other model on the bench
  • Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments

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 Opus 4.8 DeepSeek V4 Pro
VendorAnthropicDeepSeek
Context window200,000 tokens (1M with extended thinking)1,000,000-token context window
Price$15 / $75 per M tokensAPI · pro tier
Pricing detailPremium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency.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.
Release2026-052026-07
Bench coverage47/47 scored · avg 7.51/100/50 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 Opus 4.8 and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8, 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 — Opus 4.8 vs DeepSeek V4 Pro

Which is better, Opus 4.8 or DeepSeek V4 Pro?

On Goldie Bench, Opus 4.8 averages no scored verdicts yet across the shared tasks, with 3 gold, 1 silver, 1 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 Opus 4.8 cost vs DeepSeek V4 Pro?

Opus 4.8: Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. 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 Opus 4.8 vs DeepSeek V4 Pro?

Opus 4.8 has a 200,000 tokens (1M with extended thinking) context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.

When should I pick Opus 4.8 over DeepSeek V4 Pro?

Pick Opus 4.8 for: Mission-critical one-shot builds where 'has to work the first time' matters; Hard reasoning tasks (planning, multi-step) where you'll pay for the depth; Anything where vendor reliability beats the per-token bill. The trade-off is the weaknesses we logged on the bench: 5–10× the per-token cost of every other model on the bench; Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments.

When should I pick DeepSeek V4 Pro over Opus 4.8?

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 Opus 4.8 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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