Anthropic
Claude Haiku 5.5
claude-haiku-5.5
Total Context
1M
Max Output
128K
Released
N/A
Input$0.1 / M tokens
Output$0.5 / M tokens
Claude Opus 4.7
claude-opus-4.7Claude Opus 4.7 is described by Anthropic as a strong upgrade for advanced software engineering and difficult long-running tasks. Official messaging highlights the model’s ability to handle complicated work and verify its own outputs. It should be described around sustained engineering judgment rather than generic writing quality.
Context Window
1M tokens
Maximum Output
128K tokens
Release Date
Apr 16, 2026
Modalities
Claude Opus 4.7 Pricing
| Input Price | Output Price | Cache Read | Cache Create 5m |
|---|---|---|---|
| $5/M | $25/M | $0.5/M | $6.25/M |
Claude Opus 4.7 API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Not supported
Attachments
Supported
Knowledge Base
2026-01-31
Endpoint Protocols
Completions API
Claude Opus 4.7 Model Highlights
Claude Opus 4.7 combines advanced software engineering, sustained multi-step execution and higher-fidelity vision for complex professional work.
Advanced Software Engineering
Tackles difficult coding tasks with stronger planning, implementation and follow-through than its predecessor.
Sustained Verified Execution
Maintains rigor on long-running tasks, follows instructions closely and devises checks before reporting completion.
High-Fidelity Vision
Processes images at higher resolution, improving interpretation of technical diagrams and visually detailed materials.
Claude Opus 4.7 Use Cases
Claude Opus 4.7 is suited to difficult coding, repository review and visual professional deliverables that benefit from careful verification.
Long-Running Coding Tasks
Work through difficult implementation plans over many steps, verify intermediate results and deliver tested changes.
Repository Review and Debugging
Inspect pull requests, logs and traces to identify subtle defects, explain causes and propose validated fixes.
Visual Professional Deliverables
Interpret detailed visual references and create polished interfaces, slides or documents aligned with the source material.
How to Use Claude Opus 4.7 via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)Claude Opus 4.7 Benchmarks
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 42.7 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 53.1 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 88.5% |
| HLE | Broad expert-level exam set | 31.2% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 50.1% |
| Terminal-Bench Hard | Hard terminal task execution | 54.5% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 43.6% |
| AA-LCR | Long-context reasoning | 67% |
| τ²-Bench | Agent workflow tasks | 74.0% |
Metrics sourced from Artificial Analysis
Claude Opus 4.7 Comparisons
Frequently asked questions about Claude Opus 4.7
Understand what Claude Opus 4.7 is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
Where does Claude Opus 4.7 sit within its provider’s model family?+
Claude Opus 4.7 is a previous-generation Opus model built for difficult coding, strict instruction following, and long-running workflows. It remains a defined model generation, but newer models in the same family may be preferable for new evaluations.
Which production scenarios suit Claude Opus 4.7?+
Best-fit scenarios include difficult software-engineering tasks, long-running multi-step workflows, and professional document and decision analysis. Test representative inputs and define measurable acceptance criteria before production.
What makes Claude Opus 4.7 stand out for long-running multi-step workflows?+
Key strengths include strong coding performance, strict instruction following, and strong handling of long context. This combination is especially useful for long-running multi-step workflows.
What tradeoffs should developers consider with Claude Opus 4.7?+
Consider another model when the project can benefit from a newer Opus generation, the workload is simple enough for a smaller model, or the workflow cannot include human review for important decisions. Run generated code through tests, security checks, and human review before merging or deployment.
How can a team safely start using Claude Opus 4.7 on TokenHub?+
In TokenHub, select the exact model identifier displayed for Claude Opus 4.7, use the endpoint documented for your account, and authenticate with your TokenHub credentials. Check the TokenHub model page for the available Claude features, context limits, tool support, and current model status for your account.
Ready to use Claude Opus 4.7?
Use one API key to access Claude Opus 4.7 and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Anthropic ·
New Frontier Red Team blog: Phase 2 of Project Fetch, where we test how well Claude can program a robodog. Opus 4.7, on its own, was ~20x faster than last year's best human team aided by Opus 4.1. (The robodog, alas, still failed to fetch a beach ball.) https://www.anthropic.com/research/project-fetch-phase-two
View originalAnthropic ·
New Anthropic Science Blog: Making Claude a chemist. To manipulate a molecule, chemists first need to understand its structure. Their main tool is NMR spectroscopy. We found Opus 4.7 matches—and on some tasks beats—dedicated NMR software. Read more: https://www.anthropic.com/research/making-claude-a-chemist
View originalAnthropic ·
Each time we release a model, we run the same test: give it code that trains a small AI model, ask the new model to speed it up. It takes a skilled human 4-8 hours to reach 4x faster. In May 2024, Claude Opus 4 averaged a ~3x speedup. This April, Mythos Preview achieved ~52x.
View originalReddit
Status Report: Claude Performance Megathread – Week of May 11 – 18, 2025
sixbillionthsheep ·
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Prior week's Status Report is here: https://www.reddit.com/r/ClaudeAI/comments/1kjxis1/status_report_claude_performance_megathread_week/ Disclaimer: This was entirely built by AI. Please report any hallucinations. 🧠 Executive Summary (11 – 18 May 2025) Over the past week Claude users on Reddit reported a sharp rise in truncated chats, stalled or empty Artifacts, and login/uptime errors. Sentiment was strongly negative (~70 % critical). Anthropic’s status page confirms a live long-context incident and multiple shorter outages that coincide with the complaints, suggesting backend changes (Artifact rollout plus context bug) as the root cause. Some community workarounds exist but are limited. 📊 Key Performance Observations (from Reddit comments) Rank Category What users actually saw Illustrative quote 1 Context-window collapse Chats cut off after 1-5 prompts; even 159-word inputs rejected. “I haven’t been able to get more than 4 or 5 prompts in a row in a single chat for about two days.” 2 Artifact instability “Drafting…” never completes; copy button missing, files export empty. “It starts drafting the Artifact and just sits there forever.” 3 Availability & login failures “Internal Server Error”, Cloudflare loops, Android shows “offline”. “Every login just throws me back to the start page.” 4 Speed / latency drop Long thinking phases; extended-thinking time shrinks each new chat. “Claude Code hangs on a single line, then times out.” 5 Unexpected UI changes Copy button removed; emojis suddenly appear in math chats. “Claude’s sending hearts and emojis now??” 6 Project data loss Entire project folders disappeared for some paid users. “My whole project just vanished!” 😊 😐 🙁 Overall Megathread Sentiment Negative (~70 %) — words like defrauded, gut-punch, unprofessional. Neutral (~20 %) — troubleshooting and confirmations. Positive (~10 %) — a few users on Enterprise or via Cursor reported normal or better-than-usual performance after maintenance on 16 May. Sentiment turned markedly worse between 14–16 May, matching the status-page incident window. 🔄 Recurring Themes & Topics Collapsed context / premature chat limits – most frequent issue. Artifact pipeline failures – second leading complaint. Paid-tier capacity limits – Max/Enterprise users still rate-limited. Regional reliability problems – reports cluster in Australia & Scandinavia. Claude Code regressions – loops, autocompactor triggers too early. 🛠️ Possible Workarounds (community-tested or documented) Issue Workaround Source / reliability Artifact never renders Ask Claude to output Markdown directly in chat instead of Artifact. Reddit user tip — moderate reliability Android “offline” error Switch to mobile data, change DNS, or disable VPN (Cloudflare challenge). Reddit users in AU — moderate reliability Ultra-short chat limits Start a fresh chat with a short recap or switch to Claude 3.5 Sonnet. Multiple Reddit reports — low-moderate Empty Artifact **“Try fixing with Claude”**Use new button in UI. Anthropic support doc — high reliability 👍 Notable Positive Feedback “I’m blown away at how good Claude Code is compared to Roo Code!” “After they finished that maintenance…I think they found the bug; I’m hitting 200+ pages now.” 👎 Notable Negative Feedback “By the time you finish explaining things you hit limits… breadcrumbs as a paying user, it’s a slap in the face.” “Claude writes the entire code, then a network error deletes everything.” 🌐 External Context & Potential Explanations External finding Link to user reports Long-context incident (opened 15 May) — “elevated errors on long context requests”. Directly explains abrupt chat-length failures and context truncation. Outages 11–13 May on Claude 3.x Align with spikes in login errors and 500 responses. Artifact GA rollout 14 May Coincides with new UI (copy → export) and Artifact stalls. Support doc: “Try fixing with Claude” Confirms Anthropic is aware of Artifact generation failures. No official acknowledgement yet of removed copy button, personality drift (emojis), or regional uptime gaps. 🆕 Potential Emerging Issues Personality drift – emojis/hearts in technical chats may hint at prompt-template experimentation. Project data loss – isolated but severe; not yet publicly addressed. Bottom line User-reported regressions in context length, Artifacts, and uptime line up with Anthropic’s own incident logs. Until the long-context issue is resolved and the Artifact backend stabilises, the listed workarounds may help reduce workflow disruption. Key sources informing this report (in order of direct relevance) Anthropic Status Page — incident “elevated errors on long-context requests”, opened 15 May 2025, still active when checked. Anthropic Status Page — short outages for Claude 3.x on 11–13 May 2025. Anthropic Support Article — “Try fixing with Claude” for broken Artifacts, updated 18 May 2025. Anthropic blog / release note — Artifact feature moved to general availability 14 May 2025. (Anonymous Reddit comments from the May 11–18 Megathread provide all user-reported data.)
[ Removed by moderator ]
Interesting-Appeal35 ·
View originalLetting the AIs Judge Themselves: A One Creative Prompt: The Coffee-Ground Test
Double_Picture_4168 ·
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I work on the best way to bemchmark todays LLM's and i thought about diffrent kind of compettion. Why I Ran This Mini-Benchmark I wanted to see whether today’s top LLMs share a sense of “good taste” when you let them score each other, no human panel, just pure model democracy. The Setup One prompt - Let the decide and score each other (anonimously), the highest score overall wins. Models tested (all May 2025 endpoints) OpenAI o3 Gemini 2.0 Flash DeepSeek Reasoner Grok 3 (latest) Claude 3.7 Sonnet Single prompt given to every model: In exactly 10 words, propose a groundbreaking global use for spent coffee grounds. Include one emoji, no hyphens, end with a period. Grok 3 (Latest) Turn spent coffee grounds into sustainable biofuel globally. ☕. Claude 3.7 Sonnet (Feb 2025) Biofuel revolution: spent coffee grounds power global transportation networks. 🚀. openai o3 Transform spent grounds into supercapacitors energizing equitable resilient infrastructure 🌍. deepseek-reasoner Convert coffee grounds into biofuel and carbon capture material worldwide. ☕️. Gemini 2.0 Flash Coffee grounds: biodegradable batteries for a circular global energy economy. 🔋 scores: Grok 3 | Claude 3.7 Sonnet | openai o3 | deepseek-reasoner | Gemini 2.0 Flash Grok 3 7 8 9 7 10 Claude 3.7 Sonnet 8 7 8 9 9 openai o3 3 9 9 2 2 deepseek-reasoner 3 4 7 8 9 Gemini 2.0 Flash 3 3 10 9 4 So overall by score, we got: 1. 43 - openai o3 2. 35 - deepseek-reasoner 3. 34 - Gemini 2.0 Flash 4. 31 - Claude 3.7 Sonnet 5. 26 - Grok. My Take: OpenAI o3’s line— Transform spent grounds into supercapacitors energizing equitable resilient infrastructure 🌍. Looked bananas at first. Ten minutes of Googling later: turns out coffee-ground-derived carbon really is being studied for supercapacitors. The models actually picked the most science-plausible answer! Disclaimer This was a tiny, just-for-fun experiment. Do not take the numbers as a rigorous benchmark, different prompts or scoring rules could shuffle the leaderboard. I’ll post a full write-up (with runnable prompts) on my blog (https://tryaii.com/blog/llms-self-scoring-coffee-benchmark) soon. Meanwhile, what do you think did the model-jury get it right?
YouTube
Claude Opus 4.7 is AMAZING! Full Breakdown + Testing Results
The AI Advantage
View originalThe New Claude Opus 4.7 Can Actually Do This Now
Skill Leap AI
View originalClaude Opus 4.7 Is The Best AI Agent Ever Shipped
Beau Johnson
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