
GPT-5.6 Sol vs Muse Spark 1.2
OpenAI's flagship — the Sun of the 5.6 lineup. vs Meta's coding reasoning model — co-trained with its own agent, 1M-token window.
Head-to-head verdict: GPT-5.6 Sol wins 34–7 with 9 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 GPT-5.6 Sol and Muse Spark 1.2, 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%.
Muse Spark 1.2 · Cloud coder via OpenRouter; the Muse Code agent (one-command install) is its native harness.
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 Muse Spark 1.2
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, textbook synthwave scene—striped sun, layered mountains, city silhouette, palms, glowing pink-edged road with proper pseudo-3D curve and a neon car—all polished with excellent HUD and title treatment. Only minor nit is the somewhat abstract car sprite, but overall this …
What I saw: Renders a well-modeled segmented dragon with wings, glowing neon rings, cityscape depth and a clean full HUD (score/rings/velocity/combo, fury core meter, message banner, controls) that nails the brief; slightly generic minimalist environment and no visible fire-breath in this fr…
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, 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: 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…
Where Muse Spark 1.2 beat GPT-5.6 Sol
The tasks where I gave Muse Spark 1.2 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: Strong, polished dusk city that renders cleanly with third-person character, cars, pedestrians, cover crate, street lighting, and a full HUD (health/ammo/kills/cash, wanted stars, minimap). Weak point is a slightly generic blocky world and only screenshot-static evidence of shoot…
What I saw: Renders a recognizable voxel landscape with trees, water, and a polished UI, but the washed-out overexposed lighting flattens the blocks and makes water/edges read as blank white patches, hurting the crisp Minecraft look. Solid structure and clean HUD, but the visual clarity is w…
What I saw: Genuinely rendering a noisy-but-converging Cornell Box with recognizable red/green walls, area light, and metal/glass spheres — the Monte-Carlo grain and progressive accumulation read as authentic path tracing, backed by a polished UI with presets, live SPP/rays stats and a light…
What I saw: Renders cleanly with a polished HUD (altitude, vertical speed, distance-to-clearing, minimap) and a nicely deployed canopy over a vast forested landscape — on-brief for the canopy-steering phase. Slightly generic terrain and the tiny distant clearing hurt visual punch, and the at…
What I saw: Strong, polished UI with full preset/palette/slider controls and a genuinely evolving Gray-Scott sim visible in the render; the pattern looks a bit soft/blobby rather than crisp Turing structure and coverage is sparse, keeping it just short of the field's 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)
Muse Spark 1.2
Strengths
- Generative art & shader-feel scenes (fractal 8.7, aurora/galaxy/matrix/synthwave 8.6)
- Full app chrome one-shot (macOS-clone desktop 8.6)
- Fast one-shots — most builds landed in 45-80s
- 1M context for whole-repo work
Trade-offs
- 3D game worlds often render black/empty (dragonrealm 2.5, dogfight 3.0, doom 3.5)
- Open-world briefs collapse to HUD-only shells
- Reasoning tokens billed as output
Pricing & context — the spec sheet
| Spec | GPT-5.6 Sol | Muse Spark 1.2 |
|---|---|---|
| Vendor | OpenAI | Meta |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Price | $5 / $30 per M | $1.25 in / $4.25 out per 1M |
| 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. | Meta's coding-optimized reasoning model, released 2026-08-05 beside the Muse Code agent. $0.15/1M cached input. Contributor tier is token-rate-limited in a rolling 5-hour window. Benched release-day via OpenRouter (meta/muse-spark-1.2, first-party listing); Opus 4.8 judged every real rendered poster, same rubric as the whole field. |
| Release | 2026-07 | 2026-08-05 |
| Bench coverage | 50/50 scored · avg 8.16/10 | 50/50 scored · avg 7.44/10 |
The verdict — which should you pick?
Across 50 scored shared tasks, GPT-5.6 Sol averaged 8.16/10, beating Muse Spark 1.2's 7.44/10 by 0.73 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 Muse Spark 1.2 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, generative-art visuals → Muse Spark 1.2. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — GPT-5.6 Sol vs Muse Spark 1.2
Which is better, GPT-5.6 Sol or Muse Spark 1.2?
On Goldie Bench, GPT-5.6 Sol averages 8.16/10 across the shared tasks, with 3 gold, 8 silver, 12 bronze overall. Muse Spark 1.2 averages 7.44/10, with 0 gold, 3 silver, 4 bronze. GPT-5.6 Sol wins the head-to-head 34–7.
How much does GPT-5.6 Sol cost vs Muse Spark 1.2?
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. Muse Spark 1.2: Meta's coding-optimized reasoning model, released 2026-08-05 beside the Muse Code agent. $0.15/1M cached input. Contributor tier is token-rate-limited in a rolling 5-hour window. Benched release-day via OpenRouter (meta/muse-spark-1.2, first-party listing); Opus 4.8 judged every real rendered poster, same rubric as the whole field.
What's the context window for GPT-5.6 Sol vs Muse Spark 1.2?
GPT-5.6 Sol has a 1,050,000 tokens context window. Muse Spark 1.2 has a 1,000,000 tokens context window.
When should I pick GPT-5.6 Sol over Muse Spark 1.2?
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 Muse Spark 1.2 over GPT-5.6 Sol?
Pick Muse Spark 1.2 for: Generative-art visuals; Dashboard & app-shell one-shots; Long-context refactors (1M window). The trade-off is the weaknesses we logged on the bench: 3D game worlds often render black/empty (dragonrealm 2.5, dogfight 3.0, doom 3.5); Open-world briefs collapse to HUD-only shells; Reasoning tokens billed as output.
How does Goldie Bench score GPT-5.6 Sol vs Muse Spark 1.2?
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 Muse Spark 1.2 vs Fusion GPT-5.6 Sol vs Claude Opus 5 Muse Spark 1.2 vs Claude Opus 5 GPT-5.6 Sol vs Hermes MoA Muse Spark 1.2 vs Hermes MoA GPT-5.6 Sol vs Claude Fable 5 Muse Spark 1.2 vs Claude Fable 5Full model pages: GPT-5.6 Sol · Muse Spark 1.2 · 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.














































