
Real head-to-head · same prompt, one shot
Claude Opus 5 vs GPT-5.6 Sol
The new Anthropic flagship — benched on all 45 one-shot builds the day it landed. vs OpenAI's flagship — the Sun of the 5.6 lineup.
Head-to-head verdict: Claude Opus 5 wins 25–18 with 7 ties.
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 Claude Opus 5 and GPT-5.6 Sol, 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.
Claude Opus 5 · Benched on all 45 GoldieBench tasks via API on release day, incremental deploys as scores landed.
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%.
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 ↓
Claude Opus 5
GPT-5.6 Sol
Game
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Other
Where Claude Opus 5 beat GPT-5.6 Sol
The tasks where I gave Claude Opus 5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Gtafoot
Game
Claude Opus 5 8.4
·
GPT-5.6 Sol 3.5
(+4.9)
What I saw: Gorgeous dusk city with clean third-person rig, polished HUD (health/stamina/ammo/wanted stars/minimap), fountain, benches, cop car and cover props — clearly a strong shippable build. Screenshot shows no active enemies or combat in frame, so I can't confirm visible working shooti…
Voxel
Visual
Claude Opus 5 8.2
·
GPT-5.6 Sol 3.5
(+4.7)
What I saw: Strong voxel island with lush layered trees, sand beaches, tinted water and floating clouds/birds plus polished UI and controls; weakened by the harsh flat-orange sky fill that reads as a solid background rather than a sunset gradient, and the terrain is quite flat/small with no …
Pathtracer
Sim
Claude Opus 5 8.7
·
GPT-5.6 Sol 6.4
(+2.3)
· Cornell glass metals
What I saw: Strong Cornell-box render with convincing refractive glass, rough gold/aluminium metals, checkerboard floor, soft area-light shadows and visible color bleeding — a genuine progressive path tracer (102 SPP, HDR float16). Slightly noisy and the exposure looks a touch blown/washed, …
Terrain
Visual
Claude Opus 5 8.3
·
GPT-5.6 Sol 7.4
(+0.9)
What I saw: Strong island terrain with convincing height-based color ramp, sandy shores, snow-capped ridges, translucent water and a rich HUD/control panel; weak point is the flat black tree cones that read as silhouettes rather than lit foliage, slightly cheapening an otherwise polished, sh…
Lavalamp
Visual
Claude Opus 5 8.7
·
GPT-5.6 Sol 7.8
(+0.9)
· metaball lava lamp
What I saw: Gorgeous shader metaball fluid with convincing tapered glass body, glowing gold cap and ribbed metal base, plus palette switching, heat slider and pointer interaction — clearly matches the field's best. Only nit: static screenshot can't confirm morph smoothness, but the blob vari…
Where GPT-5.6 Sol beat Claude Opus 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.
Pool
Game
GPT-5.6 Sol 8.3
·
Claude Opus 5 6.0
(+2.3)
· Polished pool table
What I saw: Beautifully rendered table with realistic wood rail, felt gradient, numbered balls in a proper triangle rack, and clean HUD; physics/audio and pocketing logic are solid, though the presentation is more of an aesthetically strong standard billiards sim than a genre-redefining winner.
Arcade
Game
GPT-5.6 Sol 8.6
·
Claude Opus 5 6.5
(+2.1)
· 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.
Doom
Game
GPT-5.6 Sol 8.4
·
Claude Opus 5 6.8
(+1.6)
· 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…
Neonblaster
Game
GPT-5.6 Sol 8.3
·
Claude Opus 5 6.8
(+1.5)
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…
Neoncity
Game
GPT-5.6 Sol 8.6
·
Claude Opus 5 7.4
(+1.2)
· immersive neon drive
What I saw: Strong on-brief cyberpunk drive with lit facades in varied neon hues, receding lane markers, street lamps, and a polished HUD/title that sells the midnight-run vibe; only minor weakness is the flat road texture and slightly bare distant horizon, but overall it reads as a genuine …
Strengths & weaknesses I logged
Claude Opus 5
Strengths
- Frontier-class coding + agentic reasoning (Claude 5 family)
- 1M-token context — reads an entire codebase in one call
- Benched here with skill-infused game prompts the day of release
Trade-offs
- Premium pricing ($5/$25 per M) — route the everyday 90% to cheaper lanes
- Reasoning-by-default eats token budgets unless tuned per call
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)
Pricing & context — the spec sheet
| Spec | Claude Opus 5 | GPT-5.6 Sol |
|---|---|---|
| Vendor | Anthropic | OpenAI |
| Context window | 1,000,000 tokens | 1,050,000 tokens |
| Price | $5 / $25 per M | $5 / $30 per M |
| Pricing detail | Anthropic's brand-new flagship — the first Opus of the Claude 5 family, with a 1M-token context window. Benched via API the day it dropped; game tasks use our skill-infused AAA build prompts. | 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. |
| Release | 2026-07 | 2026-07 |
| Bench coverage | 50/50 scored · avg 8.27/10 | 50/50 scored · avg 8.16/10 |
The verdict — which should you pick?
Across 50 scored shared tasks, the averages are essentially tied — Claude Opus 5 8.27 vs GPT-5.6 Sol 8.16. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.
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 Claude Opus 5 and GPT-5.6 Sol both into the Agent Operating System and dispatch each from the kanban by task type — hardest agentic builds → Claude Opus 5, the hardest reasoning and code where being right beats being cheap → GPT-5.6 Sol. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Claude Opus 5 vs GPT-5.6 Sol
Which is better, Claude Opus 5 or GPT-5.6 Sol?
On Goldie Bench, Claude Opus 5 averages 8.27/10 across the shared tasks, with 13 gold, 7 silver, 5 bronze overall. GPT-5.6 Sol averages 8.16/10, with 2 gold, 9 silver, 12 bronze. Claude Opus 5 wins the head-to-head 25–18.
How much does Claude Opus 5 cost vs GPT-5.6 Sol?
Claude Opus 5: Anthropic's brand-new flagship — the first Opus of the Claude 5 family, with a 1M-token context window. Benched via API the day it dropped; game tasks use our skill-infused AAA build prompts. 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.
What's the context window for Claude Opus 5 vs GPT-5.6 Sol?
Claude Opus 5 has a 1,000,000 tokens context window. GPT-5.6 Sol has a 1,050,000 tokens context window.
When should I pick Claude Opus 5 over GPT-5.6 Sol?
Pick Claude Opus 5 for: Hardest agentic builds; Whole-repo reasoning; Frontier one-shots. The trade-off is the weaknesses we logged on the bench: Premium pricing ($5/$25 per M) — route the everyday 90% to cheaper lanes; Reasoning-by-default eats token budgets unless tuned per call.
When should I pick GPT-5.6 Sol over Claude Opus 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).
How does Goldie Bench score Claude Opus 5 vs GPT-5.6 Sol?
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:
Claude Opus 5 vs Fusion GPT-5.6 Sol vs Fusion Claude Opus 5 vs Hermes MoA GPT-5.6 Sol vs Hermes MoA Claude Opus 5 vs Claude Fable 5 GPT-5.6 Sol vs Claude Fable 5 Claude Opus 5 vs Qwen 3.8 GPT-5.6 Sol vs Qwen 3.8Full model pages: Claude Opus 5 · GPT-5.6 Sol · 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














































