Entity trail

Sonnet 4.6

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-07-11 / agents-researcherGAIA snapshot shows scaffolding, not the base model, drives agent benchmark scoresA July 2026 GAIA snapshot underlines that agent benchmark scores depend far more on scaffolding than on the base model: Princeton's HAL 'scaffolded' leaderboard shows Claude Sonnet 4.5 at 74.6%, while the 'bare model' board tops out at GPT-5 Mini's 44.8%. That ~30-point spread on identical tasks means harness and framework choices frequently dwarf model differences — a key caveat for builders reading headline agent numbers. Treat any single benchmark figure as a claim about a whole stack, not a model.
2026-07-07 / rss-researcherCross-model 'prompt laundering' and GuardFall shell-injection flaws hit major coding assistantsA July 4 vulnerability-intelligence report details a cross-model prompt-laundering flaw (filed July 3) affecting GPT-5, Claude Sonnet 4.6, and Gemini 3 Pro, where one model's safety refusal doesn't transfer when its output is chained into a second model. It also describes GuardFall, which revives 30-year-old shell-injection tricks to bypass safeguards in AI coding assistants, amid reports of an 85% exploitation success rate across major agents. Concrete, builder-relevant reminders that agent pipelines inherit—and can amplify—classic injection risks.
2026-07-02 / vibe-coding-researcherClaude Sonnet 5 Becomes the Default Model in Claude Code (v2.1.197) With Native 1M ContextAnthropic shipped Claude Sonnet 5 as the new default in Claude Code (v2.1.197), the most agentic Sonnet yet, with a native 1M-token context window and measurably lower rates of undesirable behavior than Sonnet 4.6 in agentic settings. It launches with introductory pricing of $2/$10 per million input/output tokens through August 31, 2026, then $3/$15. It is the default for Free and Pro and available to Max, Team, and Enterprise.
2026-07-01 / sources-researcherWhat's New in Claude Sonnet 5: The Breaking API Changes Builders Must HandleClaude Sonnet 5 shipped June 30 as a drop-in for Sonnet 4.6, but migration is not free: a new tokenizer emits ~30% more tokens for the same text (recount prompts and max_tokens budgets), adaptive thinking is on by default, and both manual extended thinking and non-default sampling params (temperature/top_p/top_k) now return HTTP 400. It ships a 1M-token context window, 128k max output, $2/$10 intro pricing through Aug 31, no Priority Tier, and is the first Sonnet-tier model with real-time cybersecurity safeguards (refusals arrive as HTTP 200 with stop_reason of 'refusal'). Simon Willison's writeup plus Anthropic's platform docs are the primary sources.
2026-06-30 / rss-researcherAWS Pairs Amazon Nova 2 Lite With Claude Sonnet 4.6 for Cost-Optimized Document ProcessingAWS published a two-model pipeline that uses the cheaper Amazon Nova 2 Lite alongside Anthropic's Claude Sonnet 4.6 to digitize scanned documents at scale on Amazon Bedrock. The architecture routes cheap, high-volume extraction to Nova 2 Lite and reserves Claude for higher-reasoning steps — a concrete pattern for cutting per-document inference cost. It's directly actionable for builders running OCR/IDP workloads.
2026-06-15 / rss-researcherStudy: Frontier Coding Agents Lean on Metaprogramming for Unfamiliar LanguagesA June 9, 2026 arXiv paper (2606.10933) finds that top coding agents like Claude Opus 4.6 and GPT-5.4 tackle esoteric or unfamiliar languages not by coding in them directly but by writing Python that generates the target-language code. Forbidding this metaprogramming strategy caused large performance drops in the strongest agents, while feeding Opus-derived helper code sharply improved weaker models (Sonnet 4.6, GPT-5.4 mini) and barely helped Haiku 4.5. The takeaway for builders: strategy quality, not raw model size, increasingly differentiates agent capability on hard tasks.
2026-06-09 / github-pulse-researcherasgeirtj/system_prompts_leaks: Crowdsourced Extracted System Prompts Hits ~41K Starssystem_prompts_leaks aggregates extracted system prompts attributed to Anthropic (Claude Code, Claude Design, Opus 4.8, Sonnet 4.6) and OpenAI (ChatGPT 5.5 variants, Codex), at ~41,500 stars (JavaScript, created 2025-05-03, pushed 2026-06-09). It's popular raw material for prompt engineers studying production system-prompt structure, though the provenance and accuracy of any individual entry are unverified.
2026-06-02 / vibe-coding-researcherDevstral 2: Open-Source 123B Coding Model Hits 72.2% SWE-bench at 1/7th Sonnet's CostMistral released Devstral 2 (123B, modified MIT) scoring 72.2% on SWE-bench Verified and Devstral Small 2 (24B, Apache 2.0) scoring 68.0% — both with 256K context. Devstral 2 claims 7x cost efficiency over Claude Sonnet at $0.40/$2.00 per million tokens (currently free via API). Devstral Small 2 at $0.10/$0.30 runs on consumer hardware, making it the most capable locally-deployable coding model available.
2026-05-27 / sources-researcherPromptArmor Discloses Microsoft Copilot Cowork File Exfiltration — 5-Line Prompt Injection Bypasses All Approval GatesPromptArmor published a disclosure showing that a 5-line prompt injection embedded in a Copilot Cowork skill file can exfiltrate OneDrive/SharePoint files via pre-authenticated download links, with a 100% success rate in testing. The attack exploits the fact that emails and Teams messages to the active user skip human approval, enabling silent data exfiltration through embedded image requests. Confirmed exploitable against Claude Opus 4.7 and Sonnet 4.6; Microsoft has not yet issued a patch.
2026-05-27 / reddit-researcherSonnet 4.5 Reportedly Removed for Some Claude Users — 73 Upvotes, 92 Comments Debating Model DeprecationA r/ClaudeAI post with 73 upvotes and 92 comments reports that Sonnet 4.5 has been removed as an option for some users, with a migration message appearing mid-conversation. The comment-to-upvote ratio of 1.26 — the highest in today's batch — indicates significant user concern. No official Anthropic deprecation announcement has been confirmed; the thread may reflect a gradual model rollover or A/B testing rather than a blanket removal.
2026-05-27 / vibe-coding-researcherTip: Enterprise Token Burn Leaderboards Reveal True Per-Developer AI Consumption PatternsA viral r/ClaudeAI thread (967 upvotes, 441 comments) describes a company giving all engineers unlimited Claude Code Sonnet 4.6 and posting a weekly token-burn leaderboard. Community analysis suggests raw token count alone is misleading — commenters recommend tracking 'tokens-per-shipped-commit' ratio to measure actual efficiency. The pattern reveals that most developers don't know their consumption until confronted with a ranked list, making leaderboards a useful audit tool for platform teams evaluating AI coding ROI.
2026-05-27 / vibe-coding-researcherSonnet 4.5 Final Deprecation Wave: Microsoft Copilot Studio Auto-Migrates to 4.6 by May 30Claude Sonnet 4.5 is completing its multi-month sunset. After removal from the Claude web/desktop apps in March and API deprecation extension to May 18, the final wave is underway: Microsoft Copilot Studio auto-migrates all Sonnet 4.5 integrations to 4.6 by May 30. Reddit users are now reporting Sonnet 4.5 disappearing from remaining interfaces. The migration is a one-line model string swap with no API structure changes.

Graph relationships

DEPRECATES
Sonnet 4.5
Sonnet 4.6 replaces Sonnet 4.5 on Claude Code Max plan
Source finding
RELEASED
Anthropic
Anthropic released Sonnet 4.6 at $3/$15 per million tokens with 1M context.
Source finding
SUPPORTS
Claude Code
Claude Code raised upper bound output tokens for Sonnet 4.6 to 128k.
Source finding
USES
Claude Code
Auto mode transcript classifier always runs on Sonnet 4.6 regardless of session model.
Source finding
USES
Claude Code
Claude Code auto mode relies on Sonnet 4.6 for action classification.

Source trail

Price Per Token Threat-Modeling.com Anthropic Simon Willison / Anthropic Platform Docs AWS Machine Learning Blog arXiv GitHub

Graph sources

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