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    April 17, 20264 min

    Claude Opus 4.7: Benchmarks, Pricing and What It Means for AI Agents in 2026

    Anthropic Claude Opus 4.7 — 87.6% on SWE-bench, best-in-class tool use, 3x vision resolution.

    Claude Opus 4.7AnthropicAI AgentsLLM BenchmarksAgentic Coding

    Released April 16, 2026 — here is what developers and AI teams need to know.

    TL;DR: Opus 4.7 jumps to 87.6% on SWE-bench Verified, leads all public models in tool use (MCP-Atlas: 77.3%), and gets 3x vision resolution — all at the same $5/$25 pricing. But web search took a hit, and a new tokenizer may increase your real costs.


    The Benchmark Numbers That Matter

    BenchmarkOpus 4.7Opus 4.6GPT-5.4Gemini 3.1 ProMythos Preview
    SWE-bench Verified87.6%80.8%80.6%93.9%
    SWE-bench Pro64.3%53.4%57.7%54.2%77.8%
    MCP-Atlas (Tool Use)77.3%75.8%68.1%73.9%
    OSWorld (Computer Use)78.0%72.7%75.0%79.6%
    GPQA Diamond94.2%91.3%94.4%94.3%94.6%
    BrowseComp (Web Search)79.3%83.7%89.3%85.9%86.9%
    CharXiv (Visual)82.1%69.1%86.1%
    HLE (no tools)46.9%40.0%42.7%44.4%56.8%

    Where Opus 4.7 Wins

    • Coding: 6.8-point jump on SWE-bench Verified — the biggest single-generation leap
    • Tool Use: Best-in-class on MCP-Atlas, beating GPT-5.4 by 9.2 points
    • Vision: 13-point jump on CharXiv, images at 2,576px resolution (3.75 megapixels)
    • Finance Agent: Leads at 64.4%, beating GPT-5.4 Pro (61.5%)

    Where It Doesn't

    • Web Research: BrowseComp dropped from 83.7% to 79.3%
    • Multilingual: Gemini 3.1 Pro still leads MMMLU at 92.6% vs 91.5%

    Pricing: Same on Paper, Different in Practice

    PlanInput (per 1M tokens)Output (per 1M tokens)
    Claude Opus 4.7$5.00$25.00
    Claude Opus 4.6$5.00$25.00

    Opus 4.7 uses a new tokenizer producing up to 35% more tokens for the same input. Net effect: fewer retries, so complex tasks often cost less overall.


    What's New Under the Hood

    1. Vision Resolution Tripled

    Images up to 2,576 pixels on the long edge (~3.75 megapixels) — more than 3x previous Claude models. One partner saw visual acuity jump from 54.5% to 98.5%.

    2. Self-Verification Loop

    The model verifies its own outputs before reporting back. Fewer hallucinated code paths, more reliable unattended execution.

    3. Production Cybersecurity Safeguards

    First Opus model with cybersecurity safeguards. Tested before rolling out to Mythos-class models.


    Opus 4.7 vs Mythos: The Real Gap

    CapabilityOpus 4.7Mythos PreviewGap
    SWE-bench Verified87.6%93.9%-6.3 pts
    HLE (with tools)54.7%64.7%-10.0 pts
    Computer Use78.0%79.6%-1.6 pts
    AvailabilityPublicPrivate (Glasswing only)

    Should You Upgrade?

    Upgrade immediately if:

    • Building coding agents or dev tools
    • Using tool-calling workflows (MCP integrations)
    • Processing screenshots or visual data
    • Need autonomous computer use

    Wait if:

    • Primary use is web research (BrowseComp regressed)
    • Heavily token-cost sensitive on simple tasks

    Migration Guide

    # Just swap the model identifier response = client.messages.create( model="claude-opus-4-7", # was claude-opus-4-6 )

    Available on: Claude.ai | API | Amazon Bedrock | Google Vertex AI | Microsoft Foundry


    FAQ

    Q: Is Opus 4.7 better than GPT-5.4? A: For coding and tool use — yes, by significant margins. For web research, GPT-5.4 Pro still leads.

    Q: Will my Opus 4.6 integrations break? A: No. API-compatible. Just swap the model identifier.

    Q: When will Mythos be publicly available? A: Not announced. Currently limited to Project Glasswing partners.


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