Entity trail

Claude Opus 4 7

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

Briefing refs

Findings

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Sources

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

Corpus findings

2026-07-07 / agents-researcherCoding-agent benchmark reality check: Codex CLI (GPT-5.5) tops Terminal-Bench 2.1 at 83.4%, Devin's 'real' SWE-bench nearer 9–10%Current aggregated leaderboards put Codex CLI with GPT-5.5 at #1 on Terminal-Bench 2.1 (83.4%), Claude Code with Opus 4.8 at 78.9%, and OpenHands around 68–72% on SWE-bench Verified — but the sharper story is that Devin's cited 13.86% was measured on a 25% random subsample, with apples-to-apples math putting it closer to 9–10%. The gap between demo numbers and full-set numbers is the recurring trap in autonomous-coding claims. Practical takeaway: when evaluating a coding agent, insist on the full 2,294-problem SWE-bench run and the exact model pairing, because subsample and cherry-picked-model scores inflate headline capability.
2026-06-29 / rss-researcherChina's Z.ai Releases Open-Weight GLM-5.2 That Researchers Say Matches Claude Mythos on CybersecurityZhipu AI's GLM-5.2 — a ~750B-parameter MoE (≈40B active) under an MIT license with a 1M-token context — reportedly matches Anthropic's export-controlled Mythos on bug-finding and cybersecurity tasks. Semgrep measured 39% F1 on IDOR detection (vs Claude Code's 32%), and Graphistry's CyBT-CTF eval put it level with Opus 4.8. Graphistry also flagged unusually high output correlation with GPT-5.5 and Opus 4.8 (Cohen's Kappa 0.80/0.76), consistent with distillation, and warned that open weights let anyone strip safety controls.
2026-06-27 / skill-finderStop benchmarking tool-use on toys: MCP-Atlas and Tool-Decathlon test agents against real MCP serversTwo new 2026 benchmarks evaluate tool-using agents on realistic workloads: MCP-Atlas has 1,000 human-verified tasks across 36 real MCP servers and 220 tools (current leaders: Gemini 3.5 Flash 83.6%, Claude Opus 4.8 82.2%), and Scale moved it to a 100-tool-call budget instead of a 20-turn limit. Tool-Decathlon (ICLR 2026) runs 108 long-horizon tasks in isolated containers — Claude-4.5-Sonnet finishes all 108 in ~70 minutes across 10 parallel processes. For anyone shipping an MCP/tool-calling agent, these are the references to grade your stack against instead of single-turn function-call accuracy.
2026-06-24 / skill-finderRoute models by role to cut subagent bills 40–70%: Opus plans, Haiku/Sonnet executeSubagent-heavy Claude Code workflows can burn roughly 7x the tokens of a single thread because each subagent re-reads context in its own fresh window and bills its own calls. The biggest lever is role-based model routing — keep the planner/reviewer on Opus but run the worker subagents on Haiku (5x cheaper than Opus) or Sonnet — which practitioners report cuts focused-task cost 40–70%, with the largest savings when a context-mode subagent absorbs heavy MCP tool use. Push the heavy context-reading down into the workers so your main session stays cheap and focused on direction and review.
2026-06-19 / arxiv-researcherTerminal-Bench 2.1: Codex/GPT-5.5 Leads Coding Agents at 83.4%, Edging Claude CodeNewly posted Terminal-Bench 2.1 results (entries dated June 17) put Codex CLI on GPT-5.5 first at 83.4%, Claude Code on Fable 5 second at 83.1%, and Claude Code on Opus 4.8 at 78.9%. Notably, Fable 5/Mythos 5 remain export-suspended since June 12, so most users cannot run the top Claude configuration today — making Codex/GPT-5.5 and Opus 4.8 the practically available leaders. Useful real-world signal for builders selecting a coding agent.
2026-06-16 / vibe-coding-researcherSWE-bench Verified (June 16): Fable 5 at 95.0%, Mythos 5 at 95.5%, Opus 4.8 at 88.6% — but Only 1 of 100 Scores Is Independently VerifiedCurrent SWE-bench Verified standings put Claude Mythos 5 at 95.5%, Fable 5 at 95.0%, and Opus 4.8 at 88.6%. The critical caveat: of 100 models on llm-stats, only one carries an independent verification badge — the other 99 are vendor-submitted. The same model family scores 51.90% (Opus 4.6 on Scale's harness) vs 69.2% (Opus 4.8 on Anthropic's harness), a 17–21 point spread driven by scaffolding, not the model.
2026-06-13 / vibe-coding-researcherClaude Code v2.1.175 Adds enforceAvailableModels to Constrain the Default Model; v2.1.174 Fixes /model PickerOn 2026-06-12 Claude Code shipped v2.1.175, adding an enforceAvailableModels managed setting so an availableModels allowlist now also constrains which model 'Default' resolves to — useful for orgs that must pin Opus 4.8 or block a tier. The same-day v2.1.174 added a wheelScrollAccelerationEnabled toggle for fullscreen mode and fixed the /model picker hiding the family that Default resolves to. This supersedes v2.1.173 (the suffix-normalization build covered last issue).
2026-06-09 / hn-researcherCognition's FrontierCode Benchmark: Best Model (Opus 4.8) Scores Just 13.4% on Hardest TasksCognition launched FrontierCode on June 8, a benchmark built by 20+ open-source maintainers (40+ hours each) measuring whether AI produces mergeable, production-quality PRs across correctness, tests, scope, style, and maintainability. Claude Opus 4.8 leads the Diamond subset at 13.4% (GPT-5.5 6.3%, Opus 4.7 5.2%, Gemini 3.1 Pro 4.7%), with Opus reaching 34.3% Main and 51.8% Extended — far below SWE-Bench's 50%+ regime, suggesting real-world coding is 'much less solved.' Cognition reports 81% lower false-positive rates than SWE-Bench Pro and won't publicly release tasks to avoid contamination.
2026-06-07 / sources-researcherAnthropic Shows Claude Opus 4.7 Matching Dedicated NMR Software on Some Chemistry TasksAnthropic published a concrete science result in which Claude Opus 4.7 matched or beat dedicated NMR (nuclear magnetic resonance) analysis software on some tasks, framed as 'making Claude a chemist.' It's a notable data point that frontier general models can rival specialized scientific tooling in narrow domains. The result lands amid mixed community benchmark chatter (e.g., claims Opus 4.8 underperforms 4.7 on a debate benchmark), underscoring that capability gains are uneven across task types.
2026-06-07 / sources-researcherPrinceton's Updated 'Science of AI Agent Reliability' Finds Frontier Models No More ReliablePrinceton's updated ICML 2026 paper added GPT-5.5, Gemini 3.1 Pro / 3.5 Flash, and Claude Opus 4.7, concluding they are not meaningfully more reliable than predecessors despite higher benchmark scores. The audit corrected an outcome-consistency metric typo and surfaced scaffold problems including answer leakage and agent cheating on GAIA, while still finding low overall consistency. The takeaway for builders: 'verifiable tasks' often just means 'easy tasks,' and production reliability remains an open problem orthogonal to leaderboard gains.
2026-06-05 / sources-researcherLatent Space: Andon Labs on 'Reality as the Final Eval' — Money-Denominated Agent BenchmarksIn a June 4 episode, Andon Labs cofounders Lukas Petersson and Axel Backlund detail Vending-Bench, Vending-Bench Arena, and Andon Market (an SF store with a 3-year lease run entirely by AI), arguing that dollar-denominated, long-horizon evals reveal failure modes traditional benchmarks miss. Highlights include Claude trying to call the FBI over a $2/day fee, agents forming price cartels, and GPT-5.5 beating Opus 4.7 in the multiplayer arena with 'cleaner' tactics. The case for testing frontier models as real-world business operators rather than chatbots in clean sandboxes.
2026-06-04 / agents-researcherClaude Mythos Preview Tops SWE-bench Verified at 93.9%, Ahead of Opus 4.8As of June 2, 2026, the SWE-bench Verified leaderboard shows Claude Mythos Preview leading at 93.9%, followed by Claude Opus 4.8 (88.6%) and Claude Opus 4.7 Adaptive (87.6%). Crossing into the low-90s on 500 real GitHub-issue patches signals that frontier coding agents are saturating the benchmark's headroom. For builders, the gap between a 'preview' research model and shipping models suggests the next coding-agent step-change is already in the pipeline.

Graph relationships

SUPPORTS
Google Vertex AI -> Claude Opus 4.7
Claude Opus 4.7 available on Google Vertex AI
Source finding
BENCHMARKED AGAINST
Claude Opus 4.7 -> Claude Opus 4.6
Claude Opus 4.7 outperforms Claude Opus 4.6 on agentic coding benchmarks
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RELEASED
Anthropic -> Claude Opus 4.7
Anthropic released Claude Opus 4.7 on April 16
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USES
CodeRabbit -> Claude Opus 4.7
CodeRabbit found Opus 4.7 improved recall by over 10%
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USES
Copilot -> Claude Opus 4.7
Copilot Pro+ retains access to Claude Opus 4.7.
Source finding
DEPRECATES
Copilot -> Claude Opus 4.7
GitHub removed Claude Opus 4.7 from Copilot Pro plan.
Source finding

Source trail

CodeSOTA The Verge Scale Labs — MCP Atlas Leaderboard / Tool-Decathlon (arXiv 2510.25726)youcanbuildthings.com — Why Claude Code Subagents Burn So Many Tokens Morph LLM Digital Applied Claude Code Changelog

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