Fusion 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 Fusion 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.

Fusion · Dispatched from Agent OS for research-heavy prompts where ensemble accuracy outweighs single-model speed.

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 Fusion beat Claude Fable 5

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

Where Claude Fable 5 beat Fusion

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, Fusion averaged 8.59/10, beating Claude Fable 5's 8.10/10 by 0.50 points. Pick Fusion 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 Fusion and Claude Fable 5 both into the Agent Operating System and dispatch each from the kanban by task type — deep-research workflows where panel consensus beats single-model answers → Fusion, 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 — Fusion vs Claude Fable 5

Which is better, Fusion or Claude Fable 5?

On Goldie Bench, Fusion averages 8.59/10 across the shared tasks, with 21 gold, 3 silver, 3 bronze overall. Claude Fable 5 averages 8.10/10, with 4 gold, 2 silver, 1 bronze. Fusion wins the head-to-head 36–7.

How much does Fusion cost vs Claude Fable 5?

Fusion: OpenRouter's Fusion API dispatches a single prompt to multiple frontier models and ensembles the answers. Premium panel: Fable 5 + GPT-5.5. Budget panel: cheaper open-weights models. Roughly half the per-token cost of a Fable 5 solo call. 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 Fusion vs Claude Fable 5?

Fusion has a Varies — depends on which panel models are dispatched context window. Claude Fable 5 has a 200,000 tokens (1M with extended thinking) context window.

When should I pick Fusion over Claude Fable 5?

Pick Fusion for: Deep-research workflows where panel consensus beats single-model answers; Cost-sensitive operators who want Fable-5-class output at ~half the bill; Production agents that benefit from vendor-redundancy on every call. The trade-off is the weaknesses we logged on the bench: Ensemble latency higher than any single model (panel calls run in parallel but the slowest still gates the response); No per-task goldiebench scoring yet — bench rank pending.

When should I pick Claude Fable 5 over Fusion?

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 Fusion 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: Fusion · Claude Fable 5 · back to the leaderboard