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

GPT-5.6 Sol vs Claude Opus 5.5

OpenAI's flagship — the Sun of the 5.6 lineup. vs Anthropic's Opus 5.5 — benched on all 50 one-shot builds, every game playtested.

Head-to-head verdict: GPT-5.6 Sol wins 44–4 with 2 ties.

GPT-5.6 Sol · context1.05M tokens
Claude Opus 5.5 · context1M tokens
GPT-5.6 Sol · price$5 / $30 per M
Claude Opus 5.5 · price$4 / $20 per M
GPT-5.6 Sol · vendorOpenAI
Claude Opus 5.5 · vendorAnthropic

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 GPT-5.6 Sol and Claude Opus 5.5, 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.

GPT-5.6 Sol · Benched on GoldieBench as the flagship Sol at medium reasoning, one-shot, then headless-playtested. In the Agent OS it's the top tier of a routed stack — Sol on the hard calls, Terra for the bulk, Luna for the everyday 90%.

Claude Opus 5.5 · Benched on all 50 GoldieBench tasks via a Claude subscription: one-shot builds, real renders, pixel-diff playtests on every game, then vision-judged.

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 ↓
GPT-5.6 Sol
Claude Opus 5.5
Game
🥈GPT-5.6 Sol on Arcade
Claude Opus 5.5 on Arcade
Game
GPT-5.6 Sol on Crypt
Claude Opus 5.5 on Crypt
Game
🥈GPT-5.6 Sol on Dogfight
Claude Opus 5.5 on Dogfight
Game
GPT-5.6 Sol on Doom
Claude Opus 5.5 on Doom
GPT-5.6 Sol on Dragonflight
Claude Opus 5.5 on Dragonflight
🥉GPT-5.6 Sol on Dragonrealm
Claude Opus 5.5 on Dragonrealm
Game
GPT-5.6 Sol on Flightsim
Claude Opus 5.5 on Flightsim
Game
GPT-5.6 Sol on Game
Claude Opus 5.5 on Game
Game
🥉GPT-5.6 Sol on Gtadrive
Claude Opus 5.5 on Gtadrive
Game
GPT-5.6 Sol on Gtafoot
Claude Opus 5.5 on Gtafoot
GPT-5.6 Sol on Neonblaster
Claude Opus 5.5 on Neonblaster
Game
GPT-5.6 Sol on Neoncity
Claude Opus 5.5 on Neoncity
Game
🥈GPT-5.6 Sol on Neonracer
Claude Opus 5.5 on Neonracer
GPT-5.6 Sol on Nordiccrypt
Claude Opus 5.5 on Nordiccrypt
Game
🥇GPT-5.6 Sol on Outrun
Claude Opus 5.5 on Outrun
Game
GPT-5.6 Sol on Parachute
Claude Opus 5.5 on Parachute
Game
🥈GPT-5.6 Sol on Pool
Claude Opus 5.5 on Pool
Game
GPT-5.6 Sol on Racing
Claude Opus 5.5 on Racing
Game
GPT-5.6 Sol on Raycaster
Claude Opus 5.5 on Raycaster
Game
GPT-5.6 Sol on Rpg
Claude Opus 5.5 on Rpg
Game
GPT-5.6 Sol on Skyrim
Claude Opus 5.5 on Skyrim
GPT-5.6 Sol on Twilightvale
Claude Opus 5.5 on Twilightvale
Game
GPT-5.6 Sol on Voxelcraft
Claude Opus 5.5 on Voxelcraft
Other
🥇GPT-5.6 Sol on Matrixrain
Claude Opus 5.5 on Matrixrain

Where GPT-5.6 Sol beat Claude Opus 5.5

The tasks where I gave GPT-5.6 Sol a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Rpg Game
GPT-5.6 Sol 8.4 · Claude Opus 5.5 5.5 (+2.9) · Polished moonlit grove

What I saw: Strong render: cohesive moonlit forest with layered trees/rocks/flowers, wandering wisp enemies, a clean HUD (HP/mana/XP/gold), quest tracker, minimap, and full control legend — clearly on-brief with combat, inventory, and loot systems in source. Slightly generic character sprite…

Doom Game
GPT-5.6 Sol 8.4 · Claude Opus 5.5 5.8 (+2.6) · polished demon raycaster

What I saw: Clean raycaster with atmospheric red-lit corridors, a well-drawn menacing demon sprite with glowing eyes and teeth, weapon viewmodel, minimap with hostile dots, and a cohesive DOOM HUD; slightly below the top only for the somewhat cartoonish monster and gradient walls that read m…

Voxelcraft Game
GPT-5.6 Sol 8.4 · Claude Opus 5.5 5.8 (+2.6)

What I saw: Renders a clean, colorful voxel world with trees, water, crosshair, hotbar and day/night HUD — clearly on-brief and polished; strong pointer-lock FPS setup with place/break and fly, though the flat pastel lighting and simple terrain keep it just shy of the top build.

Arcade Game
GPT-5.6 Sol 8.6 · Claude Opus 5.5 6.0 (+2.6) · neon breakout polish

What I saw: Gorgeous, fully-rendered neon breakout with rainbow brick grid, glowing paddle/ball, retro perspective grid floor, and clean HUD/controls/pause overlay — strong arcade identity backed by solid physics, DPR scaling, particles and audio. Polish and cohesion put it at the top of the field.

GPT-5.6 Sol 8.3 · Claude Opus 5.5 5.8 (+2.5)

What I saw: Clean render with strong neon HUD, scanline/vignette CRT overlay, glowing ship and polished starfield; source shows waves, bosses with health bars, power-ups, screen-shake, and synth music/SFX. Screenshot is a bit empty (no enemies/action visible) which slightly undersells the ju…

Where Claude Opus 5.5 beat GPT-5.6 Sol

The tasks where I gave Claude Opus 5.5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Voxel Visual
Claude Opus 5.5 7.9 · GPT-5.6 Sol 3.5 (+4.4)

What I saw: Bright, varied voxel island (15k blocks) with terraced grass, beaches, water, pastel trees, seeded regen and a day cycle. Pleasant and on-brief. Leaf blocks carry a noisy black-speckle texture and the lighting is flat midday with no fog or shadow depth, so it's below the 9.0 best.

Gtafoot Game
Claude Opus 5.5 7.6 · GPT-5.6 Sol 3.5 (+4.1)

What I saw: Playable third-person city with a jointed voxel character, crate cover, a taxi, lit windows, a round minimap, wanted stars and a clean ammo/kills HUD. The lighting is flat and pastel, there are no pedestrians or action in the mid-play frame, and the boxy low-poly look is short of…

Claude Opus 5.5 8.3 · GPT-5.6 Sol 6.4 (+1.9)

What I saw: A genuine progressive path tracer: a Cornell box with color bleeding, Fresnel glass with caustics, a mirror sphere, soft shadows, samples/paths-per-second telemetry and useful controls. At 17 spp it is still grainy, and the subtitle runs faintly into the render.

Webos Page
Claude Opus 5.5 8.7 · GPT-5.6 Sol 8.4 (+0.3)

What I saw: Polished NovaOS desktop: working Paint, Notes with a sidebar and autosave, a Terminal with neofetch/ls, a menu bar with a live clock and CPU, a side launcher and a dock with running dots, all in one cohesive macOS-like style. Very strong, but not clearly above the field's 9.0 best.

Strengths & weaknesses I logged

GPT-5.6 Sol

Strengths

  • Strong one-shot 3D games — Dragon Realm, Doom raycaster and Skyrim-lite all judged task winners
  • Whole 5.6 lineup rated High capability, even the small Luna/Terra tiers — a first for OpenAI
  • Huge ~1.05M-token context on every tier, plus a low-to-high reasoning-effort dial

Trade-offs

  • Priciest tier on the bench at $30/M output — only worth routing the hardest 10% of work to Sol
  • Reasoning can eat the token budget on big open-world briefs (one 0-byte failure until the budget was raised, then it built clean)

Claude Opus 5.5

Strengths

  • Frontier-class coding + agentic reasoning (Claude 5 family)
  • 1M-token context — reads an entire codebase in one call
  • All 50 one-shot builds rendered with zero console errors; all 23 games passed the input playtest

Trade-offs

  • Premium pricing ($4/$20 per M) — route the everyday 90% to cheaper lanes
  • One-shot builds can still ship logic bugs (e.g. a doom kill counter that miscounts)

Pricing & context — the spec sheet

Spec GPT-5.6 Sol Claude Opus 5.5
VendorOpenAIAnthropic
Context window1,050,000 tokens1,000,000 tokens
Price$5 / $30 per M$4 / $20 per M
Pricing detailGPT-5.6 shipped as three models — Luna ($1/$6 per M), Terra ($2.50/$15) and Sol ($5/$30) — each with a same-price pro variant that ships a higher default reasoning effort. All share a ~1.05M-token context window and are rated High capability. Benched here on the flagship, Sol, at medium reasoning effort via OpenRouter.Anthropic's Opus 5.5 — 1M-token context, listed at $4 input / $20 output per million tokens. Benched through a Claude subscription; game tasks use our skill-infused AAA build prompts.
Release2026-072026-09
Bench coverage50/50 scored · avg 8.16/1050/50 scored · avg 7.57/10

The verdict — which should you pick?

Across 50 scored shared tasks, GPT-5.6 Sol averaged 8.16/10, beating Claude Opus 5.5's 7.57/10 by 0.59 points. Pick GPT-5.6 Sol when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.

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 GPT-5.6 Sol and Claude Opus 5.5 both into the Agent Operating System and dispatch each from the kanban by task type — the hardest reasoning and code where being right beats being cheap → GPT-5.6 Sol, hardest agentic builds → Claude Opus 5.5. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — GPT-5.6 Sol vs Claude Opus 5.5

Which is better, GPT-5.6 Sol or Claude Opus 5.5?

On Goldie Bench, GPT-5.6 Sol averages 8.16/10 across the shared tasks, with 2 gold, 9 silver, 10 bronze overall. Claude Opus 5.5 averages 7.57/10, with 0 gold, 0 silver, 1 bronze. GPT-5.6 Sol wins the head-to-head 44–4.

How much does GPT-5.6 Sol cost vs Claude Opus 5.5?

GPT-5.6 Sol: GPT-5.6 shipped as three models — Luna ($1/$6 per M), Terra ($2.50/$15) and Sol ($5/$30) — each with a same-price pro variant that ships a higher default reasoning effort. All share a ~1.05M-token context window and are rated High capability. Benched here on the flagship, Sol, at medium reasoning effort via OpenRouter. Claude Opus 5.5: Anthropic's Opus 5.5 — 1M-token context, listed at $4 input / $20 output per million tokens. Benched through a Claude subscription; game tasks use our skill-infused AAA build prompts.

What's the context window for GPT-5.6 Sol vs Claude Opus 5.5?

GPT-5.6 Sol has a 1,050,000 tokens context window. Claude Opus 5.5 has a 1,000,000 tokens context window.

When should I pick GPT-5.6 Sol over Claude Opus 5.5?

Pick GPT-5.6 Sol for: The hardest reasoning and code where being right beats being cheap; One-shot game/sim prototypes you want shippable on the first prompt; The flagship slot in a routed Agent OS — Sol for the hard 10%, Luna/Terra for the rest. The trade-off is the weaknesses we logged on the bench: Priciest tier on the bench at $30/M output — only worth routing the hardest 10% of work to Sol; Reasoning can eat the token budget on big open-world briefs (one 0-byte failure until the budget was raised, then it built clean).

When should I pick Claude Opus 5.5 over GPT-5.6 Sol?

Pick Claude Opus 5.5 for: Hardest agentic builds; Whole-repo reasoning; Frontier one-shots. The trade-off is the weaknesses we logged on the bench: Premium pricing ($4/$20 per M) — route the everyday 90% to cheaper lanes; One-shot builds can still ship logic bugs (e.g. a doom kill counter that miscounts).

How does Goldie Bench score GPT-5.6 Sol vs Claude Opus 5.5?

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.

4,000+founders
258documented wins
38countries
$59/momonthly