GPT-5.6 Sol vs Claude Fable 5

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 Fable 5, side by side, on 47 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 Fable 5 · Selected from Agent OS for the highest-stakes work — it replaced Opus 4.8 as the safety net on hard prompts. Its four core 3D games were rebuilt to showcase quality with the threejs-game-director skill, lifting the full 42-task bench to 8.14 avg — the #1 solo model, behind only the Fusion and MoA ensembles.

Where GPT-5.6 Sol beat Claude Fable 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.

Where Claude Fable 5 beat GPT-5.6 Sol

The tasks where I gave Claude Fable 5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 47 scored shared tasks, the averages are essentially tied — GPT-5.6 Sol 8.16 vs Claude Fable 5 8.10. 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 GPT-5.6 Sol and Claude Fable 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, mission-critical one-shot builds where you want anthropic's newest reasoning → Claude Fable 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 Fable 5

Which is better, GPT-5.6 Sol or Claude Fable 5?

On Goldie Bench, GPT-5.6 Sol averages 8.16/10 across the shared tasks, with 11 gold, 11 silver, 7 bronze overall. Claude Fable 5 averages 8.10/10, with 5 gold, 1 silver, 6 bronze. GPT-5.6 Sol wins the head-to-head 31–10.

How much does GPT-5.6 Sol cost vs Claude Fable 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 Fable 5: Released alongside Mythos 5 on June 9, 2026 as the publicly-available member of the new Mythos class. Premium per-token pricing on the Anthropic API; available everywhere Opus 4.8 ships.

What's the context window for GPT-5.6 Sol vs Claude Fable 5?

GPT-5.6 Sol has a 1,050,000 tokens context window. Claude Fable 5 has a 200,000 tokens (1M with extended thinking) context window.

When should I pick GPT-5.6 Sol over Claude Fable 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 Fable 5 over GPT-5.6 Sol?

Pick Claude Fable 5 for: Mission-critical one-shot builds where you want Anthropic's newest reasoning; Long-context work using extended thinking up to 1M tokens; Plan-heavy multi-step tasks where intelligence in the plan matters more than the build. The trade-off is the weaknesses we logged on the bench: Its hardest one-shots (crypt, twilightvale) black-screened on three.js r128 API drift — the scored builds are agentic rebuilds, not the raw first pass, and crypt's AAA rebuild needed a one-line emissive patch; The showcase ceiling shown here needs the threejs-game-director scaffolding baked into the prompt — a bare one-shot lands lower (7.72 avg); Premium $10/$50 per-M pricing — you're paying for reasoning depth; cheaper models stay competitive on pure one-shot visuals.

How does Goldie Bench score GPT-5.6 Sol vs Claude Fable 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:

Full model pages: GPT-5.6 Sol · Claude Fable 5 · back to the leaderboard