
GPT-5.6 Sol vs Inkling
OpenAI's flagship — the Sun of the 5.6 lineup. vs A 975B open-weights frontier model — yours to own and run.
Head-to-head verdict: GPT-5.6 Sol wins 48–2.
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 Inkling, 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%.
Inkling · Benched on GoldieBench one-shot through Tinker's OpenAI-compatible endpoint at medium reasoning effort, then headless-playtested on the same rubric as the whole field. In the Agent OS it's wired into the opencode tab on your own Tinker key — the Ink Machine.
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 Inkling
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: Gorgeous shader render — the tilted accretion disk with fine banding, the photon-ring glow above/below the event horizon and the Doppler warm/cool gradient read as genuine gravitational lensing, all wrapped in a clean, polished HUD. Slightly weak on a distinct top-arc lensed disk…
What I saw: Strong WebGL cosine-palette plasma renders as a genuinely hypnotic, smooth fluid field with vignette and glow, plus a polished pill palette switcher and clean typography. Interactive ripples, pointer bend, keyboard shortcuts and a fallback path all present — matches the field's best.
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: a beautifully rendered 3D particle ring with glowing core, orbital rings, and gradient particle coloring, backed by a clean glassy control panel with attract/repel modes, force slider, and burst — polished and clearly on-brief. Slight weakness is the particles reading as …
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 Inkling beat GPT-5.6 Sol
The tasks where I gave Inkling a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: Renders a clean 3D voxel terrain with decent lighting, shadows, and polished UI overlay, but the random per-cube color scattering reads as noisy rather than coherent Minecraft-style biomes (grass/dirt/stone layers), and the drag-rotate control is disconnected from the actual auto…
What I saw: Renders a clean neon 3D city with roads, cover barriers, pedestrians and a wanted-star HUD, but the giant title/subtitle/DOM cover-barrier overlay dominates the frame and the scene reads generic voxel blocks rather than a polished GTA-style on-foot game; functional but not a task winner.
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)
Inkling
Strengths
- Genuinely open-weights — the full 975B model is public on Hugging Face; run it on your own key, no black box
- Best one-shot builds are 2D / animation / web — a matrix-rain that topped its task (8.4), plus arcade, fractal, aurora and a mini web-OS all judged shippable (7.6–8.2)
- Frontier-class agentic coding for an open model — 77.6% SWE-bench Verified, ahead of Nemotron 3 Ultra
- 1M-token context, native multimodal (text/image/audio), and a controllable thinking-effort dial
Trade-offs
- One-shot 3D games are weak — three.js dungeons/racers render a title screen but no playable scene, like most open models (crypt 2.5)
- Physics and particle sims are hit-or-miss — black-hole, plasma and cloth one-shots often render dark or static (2.3–3.5)
- Not the strongest overall — the closed frontier (Fable 5) still tops the raw benchmarks; Inkling trades peak for ownership
Pricing & context — the spec sheet
| Spec | GPT-5.6 Sol | Inkling |
|---|---|---|
| Vendor | OpenAI | Thinking Machines |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Price | $5 / $30 per M | $0.33 / 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. | Inkling is open-weights — a 975B-parameter (41B active) Mixture-of-Experts model whose full weights are public on Hugging Face. You run it on your own key through Tinker's OpenAI-compatible endpoint (usage-based, ~$0.33/M sampling, 50% off at launch), or via Together / Fireworks / Modal / Databricks / Baseten. Benched here one-shot at medium reasoning effort via Tinker. |
| Release | 2026-07 | 2026-07 |
| Bench coverage | 50/50 scored · avg 8.16/10 | 50/50 scored · avg 6.07/10 |
The verdict — which should you pick?
Across 50 scored shared tasks, GPT-5.6 Sol averaged 8.16/10, beating Inkling's 6.07/10 by 2.10 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 Inkling 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, owning a frontier model instead of renting one — on your own key, pennies per build → Inkling. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — GPT-5.6 Sol vs Inkling
Which is better, GPT-5.6 Sol or Inkling?
On Goldie Bench, GPT-5.6 Sol averages 8.16/10 across the shared tasks, with 11 gold, 11 silver, 7 bronze overall. Inkling averages 6.07/10, with 0 gold, 3 silver, 1 bronze. GPT-5.6 Sol wins the head-to-head 48–2.
How much does GPT-5.6 Sol cost vs Inkling?
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. Inkling: Inkling is open-weights — a 975B-parameter (41B active) Mixture-of-Experts model whose full weights are public on Hugging Face. You run it on your own key through Tinker's OpenAI-compatible endpoint (usage-based, ~$0.33/M sampling, 50% off at launch), or via Together / Fireworks / Modal / Databricks / Baseten. Benched here one-shot at medium reasoning effort via Tinker.
What's the context window for GPT-5.6 Sol vs Inkling?
GPT-5.6 Sol has a 1,050,000 tokens context window. Inkling has a 1,000,000 tokens context window.
When should I pick GPT-5.6 Sol over Inkling?
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 Inkling over GPT-5.6 Sol?
Pick Inkling for: Owning a frontier model instead of renting one — on your own key, pennies per build; Generative visuals, data-viz and single-file web builds you want one-shot; A customizable open base you can fine-tune on Tinker for your own domain. The trade-off is the weaknesses we logged on the bench: One-shot 3D games are weak — three.js dungeons/racers render a title screen but no playable scene, like most open models (crypt 2.5); Physics and particle sims are hit-or-miss — black-hole, plasma and cloth one-shots often render dark or static (2.3–3.5); Not the strongest overall — the closed frontier (Fable 5) still tops the raw benchmarks; Inkling trades peak for ownership.
How does Goldie Bench score GPT-5.6 Sol vs Inkling?
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 Inkling vs Fusion GPT-5.6 Sol vs Hermes MoA Inkling vs Hermes MoA GPT-5.6 Sol vs Claude Fable 5 Inkling vs Claude Fable 5 GPT-5.6 Sol vs Grok Inkling vs GrokFull model pages: GPT-5.6 Sol · Inkling · 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.














































