Claude Fable 5
Claude Fable 5 is Anthropic's generally available deployment of the same underlying weights as the restricted Claude Mythos 5 model. Anthropic positions the model as a new capability tier above Opus: Mythos 5 is the unsafeguarded trusted-access configuration, while Fable 5 adds production safeguards for public use. The system card reports that Mythos 5 is Anthropic's most capable model to date, with state-of-the-art results across software engineering, long-context agentic tasks, vision, knowledge work, healthcare, cyber, and life-sciences evaluations; Fable 5 matches the underlying model where safeguards do not trigger and behaves closer to Claude Opus 4.8 in safeguarded domains. Fable-specific results include SWE-Bench Verified 95.0%, SWE-Bench Pro 80.0%, Terminal-Bench 2.1 84.3% mean reward with 20.9% of trials hitting a safety fallback, OSWorld-Verified 85.0%, FrontierCode Diamond 29.3%, FrontierCode Main 46.3%, GDPval-AA 1932 Elo, GDP.pdf 29.8%, Blueprint-Bench 2 38.6%, and AutomationBench 17.4%. Fable 5 uses classifiers for cybersecurity, biology and chemistry, and distillation attempts; in Claude client apps these requests fall back to the latest Claude Opus model, while the Messages API blocks by default unless developers implement or opt into fallback. Separate competitive-use safeguards target frontier LLM development work and are estimated by Anthropic to affect about 0.03% of traffic. The model was trained on a proprietary mix of public web data, public and private datasets, and synthetic data. Anthropic prices Fable 5 at $10 per million input tokens and $50 per million output tokens, and exposes it through the Claude API as `claude-fable-5`.
Identité
| Organisation | Anthropic |
|---|---|
| Pays | — |
| Famille | — |
| Type | llm |
| Date de sortie | 2026-06-09 |
| Licence | proprietary |
| Licence commerciale | non |
| Licence open source | non |
| Poids ouverts | non |
| Auto-hébergement (DGX Spark) | non — poids fermés |
| Modalités | image|text |
| Fenêtre de contexte | 1 000 000 |
| KV cache / token (Q8) | — |
| Paramètres totaux | ≈ 5 T (estimation, confiance très faible — https://www.reuters.com/technology/bytedance-targets-mega-ai-model-nearing-anthropics-mythos-ft-reports-2026-08-07) |
| Paramètres actifs (session) | ≈ 84 B–102 B (estimation, confiance très faible — https://www.reuters.com/technology/bytedance-targets-mega-ai-model-nearing-anthropics-mythos-ft-reports-2026-08-07) |
| Source des paramètres actifs | https://www.reuters.com/technology/bytedance-targets-mega-ai-model-nearing-anthropics-mythos-ft-reports-2026-08-07 (estimation, confiance très faible) |
| Curation des paramètres actifs | 2026-10-27 |
| Prix par session | 20.00 $ (1 000 000 tokens entrée + 200 000 sortie, prix le moins cher par fournisseur) |
| Tokens / tâche (Data Players) | 1.2 M |
| Tokens / tâche (Terminal-Bench) | 57.6 M |
| Ratio Terminal-Bench / Data Players | 48.0× |
| Coût / tâche (Terminal-Bench) | 110.61 $ |
| Tokens d'entraînement | — |
| Coupure de connaissance | — |
| Créé le | 2026-06-09T20:20:02.226462Z |
| Mis à jour le | 2026-11-04T06:04:32.380323Z |
| Source | LLM Stats |
| URL | https://llm-stats.com/models/claude-fable-5 |
Prix par fournisseur
Statut du modèle (offres + auto-hébergement) : non.
Toutes sources confondues : catalogue llm-stats, routeurs EUrouter/Cortecs et catalogues directs (OVHcloud, Scaleway, Infomaniak). Les prix sont convertis en USD pour la comparaison ; le prix publié et le taux BCE utilisé sont dans l'infobulle. Les prix inconnus restent indiqués « — ».
| Fournisseur | Source | Souveraineté | Entrée (/M tok) | Sortie (/M tok) | Quantification | Contexte | Latence (s) | Débit (tok/s) | Statut |
|---|---|---|---|---|---|---|---|---|---|
| Anthropic | llm-stats | non | 10.00 $ | 50.00 $ | — | — | — | — | active |
| DeepInfra | llm-stats | non | 10.00 $ | 50.00 $ | — | — | — | — | active |
Souveraineté qualifiée par offre (modèle × fournisseur) ; survolez le badge pour les critères.
SouverainetéScores par catégorie (top_scores)
| Catégorie | Score |
|---|---|
| legal | 0.10 |
| math | 0.70 |
| multimodal | 0.50 |
| reasoning | 0.50 |
| safety | 0.80 |
| science | 0.50 |
| finance | 0.60 |
| frontend_development | 0.90 |
| general | 0.60 |
| healthcare | 0.70 |
| agents | 0.60 |
| biology | 0.50 |
| code | 0.70 |
| tool_calling | 0.50 |
| vision | 0.60 |
Scores par benchmark
| Benchmark | Catégorie | Score | Max | Normalisé (API) | Vérifié | Auto-déclaré | Daté du |
|---|---|---|---|---|---|---|---|
| automationbench | agents | 0.17 | 1.00 | 0.17 | non | oui | 2026-11-04T06:04:32.417007Z |
| biomysterybench | biology | 0.46 | 1.00 | 0.46 | non | oui | 2026-11-04T06:04:32.447847Z |
| blueprint-bench-2 | agents | 0.39 | 1.00 | 0.39 | non | oui | 2026-11-04T06:04:32.413337Z |
| deepswe-1.1 | code | 0.70 | 1.00 | 0.70 | non | non | 2026-11-04T06:04:32.483413Z |
| exploitbench | code | 0.78 | 1.00 | 0.78 | non | oui | 2026-11-04T06:04:32.458692Z |
| finance-agent-v2 | agents | 0.56 | 1.00 | 0.56 | non | non | 2026-11-04T06:04:32.470611Z |
| frontiercode | reasoning | 0.46 | 1.00 | 0.46 | non | oui | 2026-11-04T06:04:32.403524Z |
| frontiercode-1.1 | reasoning | 0.54 | 1.00 | 0.54 | non | non | 2026-11-04T06:04:32.493560Z |
| frontierswe | code | 0.90 | 1.00 | 0.90 | non | non | 2026-11-04T06:04:32.474126Z |
| gdp-pdf | general | 0.30 | 1.00 | 0.30 | non | oui | 2026-11-04T06:04:32.407921Z |
| healthbench-professional | healthcare | 0.66 | 1.00 | 0.66 | non | oui | 2026-11-04T06:04:32.466965Z |
| humanity's-last-exam | reasoning | 0.65 | 1.00 | 0.65 | non | oui | 2026-11-04T06:04:32.440631Z |
| legal-agent-benchmark | legal | 0.13 | 1.00 | 0.13 | non | oui | 2026-11-04T06:04:32.428273Z |
| lifesci-diamond-2026-11 | healthcare | 0.13 | 1.00 | 0.13 | non | non | 2026-11-04T06:04:32.503051Z |
| livebench | math | 0.78 | 1.00 | 0.78 | non | non | 2026-11-04T06:04:32.477604Z |
| osworld-verified | multimodal | 0.85 | 1.00 | 0.85 | non | oui | 2026-11-04T06:04:32.421069Z |
| swe-bench-pro | reasoning | 0.80 | 1.00 | 0.80 | non | oui | 2026-11-04T06:04:32.384731Z |
| swe-bench-verified | reasoning | 0.95 | 1.00 | 0.95 | non | oui | 2026-11-04T06:04:32.393202Z |
| terminal-bench-2.1 | reasoning | 0.84 | 1.00 | 0.84 | non | oui | 2026-11-04T06:04:32.453143Z |
| terminal-bench-4.0 | reasoning | 0.45 | 1.00 | 0.45 | non | non | 2026-11-04T06:04:32.499225Z |
Classements
| Catégorie | Rang | Score | Note conservatrice | Benchmarks évalués | Méthode | Daté du | Provenance |
|---|---|---|---|---|---|---|---|
| agents | 12 | 0.60 | 38.68 | 13 | trueskill | 2026-11-04T08:08:47.839150Z | rankings |
| code | 7 | 0.70 | 43.76 | 9 | trueskill | 2026-11-04T08:08:39.742311Z | rankings |
| math | 8 | 0.70 | 42.02 | 2 | trueskill | 2026-11-04T08:08:42.442591Z | rankings |
| multimodal | 28 | 0.50 | 31.83 | 3 | trueskill | 2026-11-04T08:08:46.488887Z | rankings |
| reasoning | 11 | 0.50 | 50.36 | 14 | trueskill | 2026-11-04T08:08:41.093494Z | rankings |
Données
Dates de curation (récupération depuis l'API) : models 2026-11-04 · benchmarks 2026-11-04 · scores 2026-11-04 · updates 2026-11-04 · account 2026-11-04 · model_history 2026-11-04 · rankings 2026-11-04