
GPT-5.6 Sol vs Claude Opus 5
OpenAI's flagship — the Sun of the 5.6 lineup. vs The new Anthropic flagship — benched on all 45 one-shot builds the day it landed.
Head-to-head verdict: GPT-5.6 Sol wins 12–0 with 1 tie.
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, side by side, on 22 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 · Benched on all 45 GoldieBench tasks via API on release day, incremental deploys as scores landed.
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 = 🥉).
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.
What I saw: Strong synthwave scene renders beautifully — retro sun with scanlines, glowing neon arches, layered city skyline, and a clean 3D car with cohesive HUD (nitro, speed, brand). Only nit is the vapor-trail particles aren't visible in this static frame, but the overall polish and on-b…
What I saw: Renders a clean, atmospheric 3D crypt with textured stone walls, pillars, archways, a floating rune and full HUD (torch bar, rune counter, controls) — a solid, shippable first-person crawler. Weakness: lighting reads more purple-lavender than 'torch-lit,' the ambient wash flatten…
What I saw: Strong: the screenshot renders a genuinely polished neon collect-and-evade game with glowing player, orbiting crystals, pulse-radius ring, HUD stats, energy bar, and clean 'Harvest the Light' title — cohesive and shippable. Weak: it's a familiar collector concept, but the executi…
What I saw: Renders cleanly with a polished, cohesive HUD—airspeed/altitude tapes, compass, throttle, nav map, brackets and flight-path marker—and a believable runway-perspective terrain with a chase-cam aircraft, hitting all brief elements (takeoff, terrain, HUD, landing assist). Loses a to…
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.
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
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
Pricing & context — the spec sheet
| Spec | GPT-5.6 Sol | Claude Opus 5 |
|---|---|---|
| Vendor | OpenAI | Anthropic |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Price | $5 / $30 per M | $5 / $25 per M |
| Pricing detail | 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. | 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. |
| Release | 2026-07 | 2026-07 |
| Bench coverage | 50/50 scored · avg 8.16/10 | 13/22 scored · avg 5.60/10 |
The verdict — which should you pick?
Across 13 scored shared tasks, GPT-5.6 Sol averaged 8.08/10, beating Claude Opus 5's 5.60/10 by 2.48 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 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. 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
Which is better, GPT-5.6 Sol or Claude Opus 5?
On Goldie Bench, GPT-5.6 Sol averages 8.08/10 across the shared tasks, with 5 gold, 12 silver, 6 bronze overall. Claude Opus 5 averages 5.60/10, with 0 gold, 0 silver, 1 bronze. GPT-5.6 Sol wins the head-to-head 12–0.
How much does GPT-5.6 Sol cost vs Claude Opus 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: 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.
What's the context window for GPT-5.6 Sol vs Claude Opus 5?
GPT-5.6 Sol has a 1,050,000 tokens context window. Claude Opus 5 has a 1,000,000 tokens context window.
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).
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.
How does Goldie Bench score GPT-5.6 Sol vs Claude Opus 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.
Related comparisons
Other head-to-heads using the same scoring system:
GPT-5.6 Sol vs Fusion Claude Opus 5 vs Fusion GPT-5.6 Sol vs Hermes MoA Claude Opus 5 vs Hermes MoA GPT-5.6 Sol vs Claude Fable 5 Claude Opus 5 vs Claude Fable 5 GPT-5.6 Sol vs Qwen 3.8 Claude Opus 5 vs Qwen 3.8Full model pages: GPT-5.6 Sol · Claude Opus 5 · back to the leaderboard
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.



































