Anthropic
Claude Haiku 5.5
Total Context
1M
Max Output
128K
Released
N/A
claude-sonnet-4.6Claude Sonnet 4.6 is presented as a broad upgrade for coding, computer use, long-context reasoning, agent planning, knowledge work, and design. Anthropic materials describe it as a strong middle tier with 1M-context beta support and better agent behavior. It is suited to teams that want near-frontier capability with more practical cost and latency than Opus.
Context Window
1M tokens
Maximum Output
64K tokens
Release Date
Feb 17, 2026
Modalities
| Input Price | Output Price | Cache Read | Cache Create 5m |
|---|---|---|---|
| $3/M | $15/M | $0.3/M | $3.75/M |
Reasoning
Tool calling
Temperature parameter
Attachments
Knowledge Base
Endpoint Protocols
Claude Sonnet 4.6 combines capable coding, long-context reasoning, computer use and design-oriented generation for balanced production workloads.
Handles complex fixes, searches large codebases and follows implementation instructions consistently.
Accepts up to one million input tokens, supporting analysis across extensive repositories and document collections.
Interprets interfaces, documents and changing screen states for computer-based tasks and visual creation.
Claude Sonnet 4.6 is suited to repository-scale fixes, enterprise document analysis and polished interface development.
Search a large repository for relevant code, diagnose a defect and implement coordinated, tested changes.
Read large collections of PDFs, charts and tables, extract relevant facts and produce a structured conclusion.
Turn product requirements and visual references into functional interfaces with considered layouts and interactions.
curl 'https://us-api.tokenhub.com/v1/messages' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY"| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 35.9 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 46.4 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 79.9% |
| HLE | Broad expert-level exam set | 13.2% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 46.9% |
| Terminal-Bench Hard | Hard terminal task execution | 46.2% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 41.2% |
| AA-LCR | Long-context reasoning | 57.7% |
| τ²-Bench | Agent workflow tasks | 79.5% |
Metrics sourced from Artificial Analysis
Understand what Claude Sonnet 4.6 is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
Claude Sonnet 4.6 is Anthropic’s current Sonnet model, balancing frontier-level coding and agent skills with lower cost than Opus. It is a current public model in its provider’s documentation, though availability can vary by platform.
Best-fit scenarios include agentic coding and repository work, computer-use and interface automation, and knowledge work across business documents. Test representative inputs and define measurable acceptance criteria before production.
Key strengths include a strong balance of quality, speed, and cost, strong coding performance, and effective use of tools and function calls. This combination is especially useful for computer-use and interface automation.
Consider another model when the task needs the strongest Opus-level capability, the workflow cannot include human review for important decisions, or a smaller Haiku model meets the quality requirement at lower cost. Run generated code through tests, security checks, and human review before merging or deployment.
In TokenHub, select the exact model identifier displayed for Claude Sonnet 4.6, 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.
Use one API key to access Claude Sonnet 4.6 and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Claude ·
Introducing Claude Sonnet 4.5—the best coding model in the world. It's the strongest model for building complex agents. It's the best model at using computers. And it shows substantial gains on tests of reasoning and math. https://t.co/7LwV9WPNAv
https://pbs.twimg.com/media/G2Bzu_jWIAAWUlK.pngView originalClaude ·
Introducing Claude Tag, a new way for teams to work with Claude. In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work. https://t.co/R2C6A5Kcye
https://pbs.twimg.com/media/HLg9iF5XYAAhaS7.jpgView originalAnthropic ·
Our latest economic research introduces a framework for tracking Claude Code as it scales. Who is using Claude Code, and what are they using it for? How is the value of tasks changing? And how much does domain expertise shape whether a session succeeds? https://www.anthropic.com/research/claude-code-expertise
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 Sonnet 4.6 Is Here (and Better Than Opus?)
Chase AI
View originalClaude Sonnet 4.6 just released. Greatest model for OpenClaw ever?
Alex Finn
View originalClaude Sonnet 4.6 in 7 Minutes
Developers Digest
View original