Real head-to-head · same prompt, one shot
Claude Fable 5 vs LongCat-2.0
The newest Anthropic model — first Mythos-class made generally available. vs The open 1.6T MoE that builds — a frontier coder trained on non-Nvidia ASIC superpods.
Head-to-head verdict: LongCat-2.0 wins 3–1.
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 Claude Fable 5 and LongCat-2.0, side by side, on 4 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.
Claude Fable 5 · Selected from Agent OS for the highest-stakes one-shot work — it replaced Opus 4.8 as the safety net on hard prompts, and the full 42-task bench run now backs that call.
LongCat-2.0 · Run through the free longcat.chat web chat (the API key had no token quota), driven with the local-model-tester GoldieBench prompts; every build render-verified + playtested (verify-move.js: walks + looks + zero errors) before scoring. Slots into the Agent OS as an open frontier coder via its OpenAI-compatible API or the Claude Code / OpenClaw / Hermes harnesses.
Side-by-side on 42 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 = 🥉).
Task ↓
Claude Fable 5
LongCat-2.0
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Where Claude Fable 5 beat LongCat-2.0
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.
Voxelcraft
Game
Claude Fable 5 8.2
·
LongCat-2.0 7.5
(+0.7)
What I saw: Strong, clean render with proper voxel terrain, a tree, working hotbar, day/night cycle, and both mouse and touch controls; weak on visual texture variety (flat Lambert colors, no block face textures) which keeps it just below the field's best.
Where LongCat-2.0 beat Claude Fable 5
The tasks where I gave LongCat-2.0 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Crypt
Game
LongCat-2.0 8.0
·
Claude Fable 5 2.0
(+6.0)
What I saw: One-shot 9KB torch-lit stone dungeon corridor — pillars, barrels, a chest, 6+ flickering torch PointLights, fog. Real WASD+mouse controls. verify-move: walks+looks, 0 errors. Lit + atmospheric (a touch over-bright orange).
Skyrim
Game
LongCat-2.0 8.5
·
Claude Fable 5 7.4
(+1.1)
What I saw: One-shot 23KB open-world explorer (the richest of the four) — rolling displaced terrain, snow mountains, a stone watchtower, 20+ conifers, boulders, grass, clouds, and terrain-height following. Real WASD+mouse. verify-move: walks+looks, 0 errors.
Dragonrealm
Game
LongCat-2.0 8.5
·
Claude Fable 5 7.8
(+0.7)
What I saw: One-shot 15KB three.js snow open-world — snow-capped mountains + 30 low-poly pines, 3000-particle falling snow, first-person glowing sword, fog. Real WASD+mouse+sprint controls, terrain-follow. verify-move: walks+looks, canvas 1440x810, 0 errors. Flawless first try — no patch.
Strengths & weaknesses I logged
Claude Fable 5
Strengths
- Best solo Anthropic model on this bench — 7.72 avg beats Opus 4.8 (7.49) and Sonnet 5 (7.18)
- Wins most head-to-heads vs every solo rival: beats Opus 4.8 on 26/42 tasks and GLM-5.2 on 27/42 — two one-shot crashes, not the craft, cost it the average
- 10 task-winner tags in a single one-shot run — shader/GPU physics is its superpower (Cornell-box path tracer 8.7, black-hole lensing 8.7, synthwave outrun 8.7)
- Tops external SWE-bench Verified at 95.0% in Julian's three-dragons writeup
Trade-offs
- Two one-shot black-screens (crypt, twilightvale) from three.js r128 API drift — called THREE.Geometry / CapsuleGeometry, which the pinned CDN doesn't have
- Free GLM-5.2 still edges it on creative one-shots (7.77 vs 7.72) at $0 — the $10/$50 premium buys agentic depth, not one-shot visuals
LongCat-2.0
Strengths
- One-shot GoldieBench: 3 of 4 flawless playable 3D builds (Dragon Realm 8.5, Skyrim 8.5, Crypt 8.0); Voxel Craft built one-shot but needed a 1-line camera fix (7.5) — avg 8.1
- 1.6T-param MoE (~48B active/token) with LongCat Sparse Attention + a 1M-token window — built for long-horizon agentic + coding tasks
- Open weights, deeply integrated with Claude Code, OpenClaw and Hermes — a free frontier-class coder to slot into the Agent OS
Trade-offs
- The direct API key we were given had near-zero token quota, so we ran it through the free web chat rather than the API
- One camera-framing miss: Voxel Craft loaded facing away from the world (sky-only) until a one-line yaw/pitch patch pointed it at the terrain
Pricing & context — the spec sheet
| Spec | Claude Fable 5 | LongCat-2.0 |
|---|---|---|
| Vendor | Anthropic | Meituan |
| Context window | 200,000 tokens (1M with extended thinking) | 1,000,000 tokens (LongCat Sparse Attention) |
| Price | $10 / $50 per M tokens | Open weights · free web chat · API |
| Pricing detail | 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. | LongCat-2.0 is open-sourced (weights on Hugging Face + GitHub) and served via the longcat.chat web chat plus an OpenAI-compatible API (model id 'LongCat-2.0' at api.longcat.chat/openai/v1). It's a 1.6T-parameter MoE with ~48B activated per token, trained entirely on AI ASIC superpods (>50K accelerators, 35T+ tokens, no rollbacks). Note: the direct API key we were handed shipped with zero token quota ('Token 额度不足'), so every build here was run through the free web chat. Vendor: Meituan. |
| Release | 2026-06-09 | 2026-06 |
| Bench coverage | 42/42 scored · avg 7.72/10 | 4/4 scored · avg 8.12/10 |
The verdict — which should you pick?
Across 4 scored shared tasks, LongCat-2.0 averaged 8.12/10, beating Claude Fable 5's 6.35/10 by 1.78 points. Pick LongCat-2.0 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 Claude Fable 5 and LongCat-2.0 both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where you want anthropic's newest reasoning → Claude Fable 5, one-shot single-file 3d / html / game builds inside the agent os → LongCat-2.0. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.
FAQ — Claude Fable 5 vs LongCat-2.0
Which is better, Claude Fable 5 or LongCat-2.0?
On Goldie Bench, Claude Fable 5 averages 6.35/10 across the shared tasks, with 3 gold, 1 silver, 7 bronze overall. LongCat-2.0 averages 8.12/10, with 0 gold, 1 silver, 2 bronze. LongCat-2.0 wins the head-to-head 3–1.
How much does Claude Fable 5 cost vs LongCat-2.0?
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. LongCat-2.0: LongCat-2.0 is open-sourced (weights on Hugging Face + GitHub) and served via the longcat.chat web chat plus an OpenAI-compatible API (model id 'LongCat-2.0' at api.longcat.chat/openai/v1). It's a 1.6T-parameter MoE with ~48B activated per token, trained entirely on AI ASIC superpods (>50K accelerators, 35T+ tokens, no rollbacks). Note: the direct API key we were handed shipped with zero token quota ('Token 额度不足'), so every build here was run through the free web chat. Vendor: Meituan.
What's the context window for Claude Fable 5 vs LongCat-2.0?
Claude Fable 5 has a 200,000 tokens (1M with extended thinking) context window. LongCat-2.0 has a 1,000,000 tokens (LongCat Sparse Attention) context window.
When should I pick Claude Fable 5 over LongCat-2.0?
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: Two one-shot black-screens (crypt, twilightvale) from three.js r128 API drift — called THREE.Geometry / CapsuleGeometry, which the pinned CDN doesn't have; Free GLM-5.2 still edges it on creative one-shots (7.77 vs 7.72) at $0 — the $10/$50 premium buys agentic depth, not one-shot visuals.
When should I pick LongCat-2.0 over Claude Fable 5?
Pick LongCat-2.0 for: One-shot single-file 3D / HTML / game builds inside the Agent OS; Long-context, repo-level edits + automated agentic task execution; A free, open, frontier-class coder to drop into the Model-Proof System. The trade-off is the weaknesses we logged on the bench: The direct API key we were given had near-zero token quota, so we ran it through the free web chat rather than the API; One camera-framing miss: Voxel Craft loaded facing away from the world (sky-only) until a one-line yaw/pitch patch pointed it at the terrain.
How does Goldie Bench score Claude Fable 5 vs LongCat-2.0?
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:
Claude Fable 5 vs Fusion LongCat-2.0 vs Fusion Claude Fable 5 vs Hermes MoA LongCat-2.0 vs Hermes MoA Claude Fable 5 vs Grok LongCat-2.0 vs Grok Claude Fable 5 vs MiniMax M3 LongCat-2.0 vs MiniMax M3Full model pages: Claude Fable 5 · LongCat-2.0 · back to the leaderboard
The same stack Julian uses
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 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.
3,600+founders
258documented wins
38countries
$59/momonthly