le définitif sommet du Claude 4 génération, integrating dynamic cognitif raisonnement profondeur, un 1M token contexte, et optional rapide inférence modes.
Technical Specifications
- Provider
- Anthropic
- Category
- flagship
- Release Date
- 2026-05
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- $20 / month
- Reasoning Effort Control
- Configurable (Low / Med / High)
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- claude-opus-4-8-20260501
- Supported SDK & API Protocol
- Anthropic Messages API + AWS Bedrock + Vertex AI
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2028+)
- Production Rate Limits (RPM & TPM)
- 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
- Prompt Cache Write & TTL Policy
- $0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
- Computer Use & Browser GUI Agent
- Supported (Screen coordinate grounding, browser & desktop GUI action loops)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Native Web Search Citations + Code Execution Tool + MCP Connectors
- Fine-Tuning & Distillation Support
- Custom Model Tuning via Amazon Bedrock & Prompt Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Anthropic Cloud API
- System Card & Safety Framework
- Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Claude Opus 4.8 Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~19 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Claude Opus 4.8:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 80.8%
- GPQA Diamond
- 78.9%
- MMLU-Pro
- 89.6%
- HumanEval
- 96.7%
- Terminal-Bench
- 54.2%
- Chatbot Arena Elo
- 1420pts
Strengths
- sommet benchmark performances du Claude 4 series à travers tous raisonnement et mathématiques metrics
- Introduced rapide inférence palier reducing TTFT sur standard conversationnel turns
- inégalé multi-étapes autonome planning pour complexe agent swarms
Limitations & Trade-offs
- Expensive sortie token génération pour élevé-volume non-critical flux de travail
- Significant matériel resource requirements during sommet pensée effort
Editorial Assessment
le apex du Claude 4 architecture before le Claude 5 paradigm shift.
Best for: de pointe AI recherche, multi-agent systems orchestration, et d'entreprise ingénierie logicielle
Compare Claude Opus 4.8
Frequently Asked Questions about Claude Opus 4.8
How much does the Claude Opus 4.8 API cost per 1M tokens?+
Claude Opus 4.8 by Anthropic is priced at $5 per 1M input tokens and $25 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.5 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Claude Opus 4.8 pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Claude Opus 4.8's context window?+
Claude Opus 4.8 features a 1M tokens context window, which equals approximately 750,000 English words or ~2,000 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 128,000 tokens.
Can I run Claude Opus 4.8 locally on my own GPU (Open Weights)?+
No, Claude Opus 4.8 is a proprietary closed-weights model hosted by Anthropic. It cannot be downloaded for local GPU execution and must be accessed via Anthropic's official API or cloud platform.
Does Anthropic train on data sent to the Claude Opus 4.8 API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Anthropic Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Anthropic API, AWS Bedrock, Google Cloud Vertex AI.
How does Claude Opus 4.8 perform on coding and reasoning benchmarks?+
Claude Opus 4.8 achieves a composite Intelligence Index of 67/100, scoring 80.8% on SWE-bench Verified, 78.9% on GPQA Diamond, 89.6% on MMLU-Pro, and 1420 pts on Chatbot Arena Elo.
What is Claude Opus 4.8 best used for?+
Claude Opus 4.8 is best suited for: de pointe AI recherche, multi-agent systems orchestration, et d'entreprise ingénierie logicielle. Assessment: le apex du Claude 4 architecture before le Claude 5 paradigm shift.
Anthropic Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Anthropic's flagship reasoning tier:
Claude Haiku 5.5
Claude Opus 5.5
Claude Mythos 5.1
Claude Fable 5.1
Claude Sonnet 5.5
Claude Opus 5
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Claude Opus 4.8:
L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.
Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).
Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.
Un modèle d'IA entraîné par apprentissage par renforcement pour allouer du temps de calcul à la réflexion logique avant d'émettre une solution, idéal pour les problèmes scientifiques et le code complexe.
Une méthode de raisonnement pas-à-pas où le modèle décompose le problème en étapes logiques intermédiaires avant de conclure, augmentant drastiquement la précision en mathématiques et programmation.
La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.
Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.