
GPT-5.6 Sol vs Grok 4.6
OpenAI's flagship — the Sun of the 5.6 lineup. vs Frontier intelligence at half the frontier price.
Head-to-head verdict: GPT-5.6 Sol wins 18–2.
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 Grok 4.6, side by side, on 20 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%.
Grok 4.6 · Benched on 16 skill-infused game builds, every one played through its full gameplay arc before scoring, then the broken ones were handed back to Grok 4.6 to repair itself.
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 Grok 4.6
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 on-brief 3D first-person Skyrim-lite: snowy low-poly terrain, distant mountains, pine forest, a stone keep, first-person sword, and a full themed HUD (compass, quest tracker, health/stamina bars). Cohesive and shippable, though the snowy foreground reads a bit washed-out/f…
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.
What I saw: Strong architectural depth with pillars, wooden crossbeams, glowing runes, torches and a distant shrine/portal that reads clearly as an ancient Nordic ruin, plus polished HUD framing. But the lighting is too bright/washed-out for a 'torch-lit dungeon' — it lacks the dark, atmosph…
What I saw: Beautifully rendered third-person chase-cam scene with a detailed player jet, layered clouds, moon, enemy squadron inbound, and a cohesive HUD (crosshair, armor/boost meters, working radar with blips). Cinematic art direction and complete combat framing make it a clear task winne…
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…
Where Grok 4.6 beat GPT-5.6 Sol
The tasks where I gave Grok 4.6 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: Third-person street level with a real armed character model, long cast shadows, a sunset skybox, pedestrians and parked cars down the block, plus a grid minimap. Played 12s: AMMO went 11 to 09 and SCORE 000010 to 000030 on click-fire, so shooting and scoring are wired. World is b…
What I saw: Strong: a fully-rendered 3D breakout with atmospheric cityscape, glowing rails, detailed paddle craft, brick grid, active ball with particle trail, and polished HUD (core/velocity/lives/score/wave). Weak: perspective makes the brick field feel small and the 3D angle slightly comp…
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)
Grok 4.6
Strengths
- Ties GPT-5.6 Sol at 61 on the Artificial Analysis Intelligence Index, one point behind Claude Fable 5 Max
- Trained with agentic reinforcement learning for long-running agents, so it holds a spec across a 40KB single-file build
- Fixes its own broken builds: handed the exact runtime error, it repaired 4 of 4 failed games on the first retry
- Very strong arcade and shooter output - the synthwave racer and the Doom raycaster are top-tier one-shots
Trade-offs
- Flight models are its weak spot: both the flight sim and the dogfight shipped unflyable on the first pass
- Two of sixteen game builds died on a hard error (a duplicate identifier and a bad computeBoundingSphere call)
- Worlds are lit and composed but usually untextured, so terrain reads as flat coloured planes
Pricing & context — the spec sheet
| Spec | GPT-5.6 Sol | Grok 4.6 |
|---|---|---|
| Vendor | OpenAI | xAI |
| Context window | 1,050,000 tokens | 500,000 tokens |
| Price | $5 / $30 per M | $2 in / $6 out per M tokens |
| 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. | xAI's August 2026 flagship. $2 per million input tokens and $6 per million output tokens on the standard tier (the Fast tier is double), which is roughly half what the other frontier models charge for the same Artificial Analysis Intelligence Index score of 61. |
| Release | 2026-07 | 2026-08 |
| Bench coverage | 50/50 scored · avg 8.16/10 | 20/20 scored · avg 5.95/10 |
The verdict — which should you pick?
Across 20 scored shared tasks, GPT-5.6 Sol averaged 8.12/10, beating Grok 4.6's 5.95/10 by 2.17 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 Grok 4.6 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, high-volume agent work where the per-token bill decides what you can afford to run → Grok 4.6. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — GPT-5.6 Sol vs Grok 4.6
Which is better, GPT-5.6 Sol or Grok 4.6?
On Goldie Bench, GPT-5.6 Sol averages 8.12/10 across the shared tasks, with 2 gold, 9 silver, 12 bronze overall. Grok 4.6 averages 5.95/10, with 1 gold, 0 silver, 0 bronze. GPT-5.6 Sol wins the head-to-head 18–2.
How much does GPT-5.6 Sol cost vs Grok 4.6?
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. Grok 4.6: xAI's August 2026 flagship. $2 per million input tokens and $6 per million output tokens on the standard tier (the Fast tier is double), which is roughly half what the other frontier models charge for the same Artificial Analysis Intelligence Index score of 61.
What's the context window for GPT-5.6 Sol vs Grok 4.6?
GPT-5.6 Sol has a 1,050,000 tokens context window. Grok 4.6 has a 500,000 tokens context window.
When should I pick GPT-5.6 Sol over Grok 4.6?
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 Grok 4.6 over GPT-5.6 Sol?
Pick Grok 4.6 for: High-volume agent work where the per-token bill decides what you can afford to run; Arcade, shooter and driving builds in one shot; Self-repair loops - it is unusually good at fixing a build when you hand it the real error. The trade-off is the weaknesses we logged on the bench: Flight models are its weak spot: both the flight sim and the dogfight shipped unflyable on the first pass; Two of sixteen game builds died on a hard error (a duplicate identifier and a bad computeBoundingSphere call); Worlds are lit and composed but usually untextured, so terrain reads as flat coloured planes.
How does Goldie Bench score GPT-5.6 Sol vs Grok 4.6?
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 Grok 4.6 vs Fusion GPT-5.6 Sol vs Claude Opus 5 Grok 4.6 vs Claude Opus 5 GPT-5.6 Sol vs Hermes MoA Grok 4.6 vs Hermes MoA GPT-5.6 Sol vs Claude Fable 5 Grok 4.6 vs Claude Fable 5Full model pages: GPT-5.6 Sol · Grok 4.6 · 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.










































