Claude Opus 4

Tekst i chatPovučenoNije dostupno
od AnthropicID modela: claude-opus-4

Anthropic's most powerful model. Exceptional at complex analysis, agentic tasks, and extended reasoning.

Status
Nije dostupno
Kontekst
200.000 tokena
Maks. izlaz
32.000 tokena
Ulaz → izlaz
Tekst → Tekst
Razvojni inženjer
Anthropic
Ažurirano
23. septembar 2026.

Claude Opus 4 trenutno nije dostupan

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Dostupna je novija verzija: Claude Opus 4.8

01

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Playground

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Razgovor

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03

O Claude Opus 4

UkratkoStanje: 23. septembar 2026.

Claude Opus 4 je model od Anthropic iz kategorije Tekst i chat. Claude Opus 4 trenutno nije dostupan na Railwailu. Kontekstni prozor sadrži 200.000 tokena, a jedan odgovor može biti dugačak do 32.000 tokena. Novija verzija: Claude Opus 4.8.

Pozadina

O Anthropic

Osnovano 2021 · San Francisco, USA

Anthropic was founded in 2021 by Dario Amodei (CEO) and Daniela Amodei (President) after both left OpenAI together with several senior researchers including Tom Brown, Sam McCandlish and Jared Kaplan. The company is structured as a Public Benefit Corporation focused on AI safety research and the deployment of reliable, interpretable, and steerable AI systems. Anthropic's foundational research includes Constitutional AI (2022), Sparse Autoencoders for interpretability, and the influential paper 'Scaling Laws for Neural Language Models'. The Claude model family launched in March 2023, with major releases including Claude 2 (2023), Claude 3 family (Haiku, Sonnet, Opus in March 2024), Claude 3.5 Sonnet (June 2024), Claude 3.7 Sonnet with extended thinking (February 2025) and Claude 4 family (May 2025). Investors include Google ($3B+), Amazon (committed up to $8B), Spark Capital and Lightspeed, with total funding exceeding $15 billion and a 2025 valuation above $60 billion. Anthropic also publishes Responsible Scaling Policies and is a leading voice in ASL safety levels.

Posjetite Anthropic

Arhitektura

Decoder-only Transformer (frontier reasoning model)

Claude Opus 4 is Anthropic's flagship reasoning model released in May 2025, optimized for agentic coding, multi-hour autonomous tasks and deep research. It uses a decoder-only Transformer architecture trained on a diverse multilingual corpus including curated web data, code repositories, books and licensed datasets, with an explicit data cutoff of March 2025. The model is post-trained with a combination of Reinforcement Learning from Human Feedback (RLHF), Constitutional AI (CAI) and Reinforcement Learning from AI Feedback (RLAIF), where a constitution of principles guides self-critique and revision. Opus 4 supports two operating modes: standard fast responses and extended thinking mode in which the model produces an internal reasoning trace before its final answer. Tool use, parallel tool calling and long-running agent loops are first-class behaviours, with native support for Anthropic's computer use API (screen control, mouse, keyboard). Vision grounding was trained jointly with text so that images, charts and PDFs can be reasoned about within the same context window. The model was evaluated against ASL-3 safeguards under Anthropic's Responsible Scaling Policy and shipped with classifier-based safety filters covering CBRN, cyberweapons, and child safety.

Parametri
Undisclosed (estimated multi-hundred billion parameters dense)
Kontekst
200.000 tokena

Mogućnosti

  • State-of-the-art coding performance on SWE-bench Verified (~72% on agentic eval at launch)
  • Extended thinking mode for chain-of-thought reasoning on hard math and science problems
  • Sustained multi-hour autonomous coding sessions with tool use and self-correction
  • Native computer use: screenshots, mouse and keyboard control of a virtual desktop
  • 200K token context window with strong needle-in-haystack recall across the full window
  • Multimodal input: text, images, PDFs, charts and diagrams in a single prompt
  • Parallel tool calling and stable multi-turn agent loops
  • Constitutional-AI alignment with low refusal rate on benign questions
  • Strong instruction following including XML tags, schemas and strict JSON output
  • Multilingual fluency across English, German, French, Spanish, Japanese, Chinese and more
  • Best for: complex coding agents, research synthesis from large document sets, regulated-industry copilots, autonomous workflows.

Obuka i licenca

Pretrained on a curated mix of publicly available internet text, licensed third-party data, code from public repositories and human-generated conversations. Anthropic does not disclose exact token counts but the corpus is multi-trillion tokens with heavy filtering for quality, deduplication and copyright. The data cutoff is March 2025. Post-training uses RLHF, Constitutional AI and RLAIF on a much smaller, high-quality set of human-rated comparisons and synthetic constitutional critiques.

Licenca: Proprietary commercial license via Anthropic API, Amazon Bedrock and Google Vertex AI. Commercial use permitted under Anthropic's Usage Policy.

Testiranje sigurnosti: Deployed under Responsible Scaling Policy ASL-3 safeguards with constitutional classifiers, automated red-teaming, third-party evaluations by METR and Apollo Research, and a Bug Bounty programme.

Poznata ograničenja

  • No native audio or video input
  • Knowledge cutoff March 2025; lacks real-time information without tool use
  • Higher latency and cost than Sonnet/Haiku tiers
  • Will refuse some legitimate red-team and security research prompts
  • No fine-tuning available to external customers
04

Cijene

Trenutno nedostupno. Za ovaj model trenutno nema cijene, pa se ne može pokrenuti.

05

API

Pozovi Claude Opus 4 sa svojim Railwail API ključem. Koristi ovaj ID modela u zahtjevu:

Trenutno nije dostupno

Model nema provjeren cijenu ili je deaktiviran; API pozivi se odbijaju.

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Specifikacije

ID modela
claude-opus-4
Razvojni inženjer
Anthropic
Kategorija
Tekst i chat
Ulaz
Tekst
Izlaz
Tekst
Kontekstni prozor
200.000 tokena
Maks. izlaz
32.000 tokena
Životni ciklus
Povučeno
Veličina modela
Undisclosed (estimated multi-hundred billion parameters dense)
Licenca
Proprietary commercial license via Anthropic API, Amazon Bedrock and Google Vertex AI. Commercial use permitted under Anthropic's Usage Policy.
Katalog ažuriran
23. septembar 2026.

Oznake

  • flagship
  • reasoning
  • agentic
07

Primjer promptova

Primjeri iz Railwail kataloga. Nisu generirani uživo na ovoj stranici.
  • Deep Research

    Analyze the economic implications of universal basic income. Consider arguments from both proponents and critics, citing specific pilot programs.
    Prikaži primjer odgovora

    UBI has been tested in several notable pilot programs with mixed but informative results. Finland's 2017-2018 experiment gave 2,000 unemployed citizens €560/month and found improved well-being and modest employment gains, though critics noted the small sample size. Stockton, California's SEED program ($500/month to 125 residents) showed recipients were more likely to find full-time employment than the control group, challenging the 'laziness' argument. Proponents argue UBI provides a safety net that encourages entrepreneurship and addresses job displacement from automation. Critics counter that large-scale funding—estimated at $3+ trillion annually for the US—would require massive tax restructuring, and inflationary pressures could erode the benefit's purchasing power.

  • Agentic Planning

    I need to migrate a monolithic Django app to microservices. Create a step-by-step migration plan with risk mitigation strategies.
    Prikaži primjer odgovora

    Phase 1 (Weeks 1-4): Audit and map all domain boundaries in your monolith. Identify bounded contexts using domain-driven design principles. Document all inter-module dependencies and shared database tables. Phase 2 (Weeks 5-8): Implement the Strangler Fig pattern—deploy an API gateway that routes traffic to either the monolith or new services. Extract the least-coupled domain first (often authentication or notifications) as a proof of concept. Phase 3 (Weeks 9-16): Gradually extract remaining services. For each: create a dedicated database, implement an anti-corruption layer for data sync, and use event-driven communication (Kafka/RabbitMQ) instead of synchronous calls. Risk mitigation: Run services in parallel with the monolith ('dark launching') before cutting over. Implement distributed tracing (Jaeger/Zipkin) from day one. Keep rollback paths open by maintaining the monolith until each service proves stable in production for at least 2 sprint cycles.

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Primjena

Za što se koristi

  • Autonomous software engineering agents
  • Long-document legal and financial analysis
  • Scientific research synthesis
  • Regulated-industry customer support copilots
  • Computer-use automation
  • Complex multi-step planning
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Često postavljana pitanja

Što je Claude Opus 4?

Claude Opus 4 je model od Anthropic iz kategorije Tekst i chat. Naveden je na Railwailu, ali se trenutno ne može pokrenuti.

Koliko stoji Claude Opus 4 na Railwailu?

Claude Opus 4 se trenutno ne može pokrenuti na Railwailu, pa nema trenutne cijene. Dostupne alternative s cijenama navedene su dalje na ovoj stranici.

Koliki je kontekstni prozor od Claude Opus 4?

Kontekstni prozor od Claude Opus 4 sadrži 200.000 tokena. Jedan odgovor može biti dugačak do 32.000 tokena.

Koliko je brz Claude Opus 4?

Za Claude Opus 4 na Railwailu još nema dovoljno izmjerenih pokretanja da bi se navedlo vrijeme izvršavanja. Ovisi o unošenju, postavkama i opterećenju kod pružatelja.

Je li Claude Opus 4 bolji od Claude Opus 4.8?

To ovisi o zadatku. Claude Opus 4 (Anthropic) i Claude Opus 4.8 (Anthropic) su oba modela iz kategorije Tekst i chat. Stranica za usporedbu prikazuje njihove cijene i specifikacije usporedno.

Usporedi Claude Opus 4 i Claude Opus 4.8

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