Entity trail

Claude Opus 4.8

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

2026-08-07 / rss-researcherPinning Claude Code to one AWS region: Mantle covers seven, classic Bedrock covers only LondonAWS published two concrete recipes on August 6 for regulated customers who need Claude Code inference to stay in a single region rather than merely in-geography, since cross-Region inference is the throughput-friendly default. Path one sets `CLAUDE_CODE_USE_MANTLE=1` plus `AWS_REGION` and pins models by plain ID (e.g. `anthropic.claude-opus-4-8`), with in-region support in Ireland, Stockholm, Tokyo, Melbourne, N. Virginia, Ohio, and Oregon. Path two uses classic Bedrock with application inference profile ARNs, but only eu-west-2 (London) currently supports Opus 4.6 and Sonnet 4.6 in-region.
2026-08-07 / hn-researcherQwen3.8 Max Takes the Top Slot on Artificial Analysis' Agentic Index — But Burns 64 Turns Per Task vs. Qwen3.7's 14Qwen3.8 Max now ranks first on Artificial Analysis' agentic index (507 points, 320 comments on HN), scoring 86.1 on OSWorld-Verified ahead of GPT-5.6 Sol Max (83.2) and Fable 5 (85.0), at $2.00/M input and $6.00/M output. Its Intelligence Index score of 56 puts it level with Claude Opus 4.8 (max) and ahead of every model from Google, Meta and xAI. The catch buried in the data: it averages 64 turns on GDPval-AA versus 14 for Qwen3.7 Max, so the headline agentic win comes with a ~4.5x turn-count tax that a per-token price comparison hides entirely.
2026-08-07 / github-pulse-researcherRealReplicaBench Puts Claude Opus 5 on Top at 61.7% Across 107 Long-Horizon Tasks in Cloned Commerce ServicesAccio-org/RealReplicaBench (created 2026-08-02, 1,038 stars in 5 days) benchmarks agents against high-fidelity stateful replicas of eight commerce and logistics platforms — Alibaba-style publishing, FreightOS-style freight, Shopify-style storefront admin — over 107 tasks (53 CLI, 28 browser, 16 file, 10 API/MCP). Twelve models were run on two harnesses: Claude Opus 5 leads at 66/107 (61.7%) on the Accio harness and 60/107 (56.1%) on OpenClaw, ahead of Opus 4.8 (55.1%/51.4%) and GPT-5.6 Sol (49.5%). The harness swap moves scores by 5+ points on identical models — a reminder that agent scaffolding is a measured variable, not a footnote.
2026-08-07 / sources-researcherxAI Ships Grok 4.6 on the Same 1.5T Foundation as 4.5 — With No Model Card, No Benchmarks, and a 2.1T Grok 4.7 Already Teed UpGrok 4.6 launched Aug 7 reusing the 1.5-trillion-parameter V9 foundation from Grok 4.5, with gains attributed entirely to improved supervised fine-tuning and RL rather than scale. As of launch xAI has published no benchmarks, model card, or scores, so every number circulating is speculation until independent Arena results land next week; for reference Grok 4.5 (high) sits at 54 on the Artificial Analysis Intelligence Index, fourth behind Claude Fable 5, GPT-5.5 and Claude Opus 4.8. A larger 2.1T-parameter Grok 4.7 is expected within weeks. Flagged low because the primary source is secondary reporting and xAI has published nothing verifiable.
2026-08-06 / skill-finderPlant canary tools in your registry to audit tool-selection reasoning — susceptibility spans 36x across models and the worst hosted model is mid-tier, not cheapCanary tools are deliberate decoys covering six weakness types (semantic decoys, parameter traps, capability mirages, prerequisite blindness, temporal decoys, granularity traps). Across 8 models, 120 tasks, 8,640 runs and 2,880 ablation runs, susceptibility varied about 36x — lowest for Claude Opus 4.8, highest for Llama 3.1 8B — and correlated with task failure at Spearman rho = -0.34. Softening the decoy's wording left frontier susceptibility essentially unchanged, so this is a reasoning failure, not phrase matching; capability tier alone does not predict safety.
2026-08-06 / reddit-researcherClaude Opus 4.1 Is Now Fully Retired — Requests to claude-opus-4-1-20250805 Return an ErrorThe August 5 platform release notes confirm the model is no longer served at all: all requests error out, with Anthropic recommending Opus 5 and pointing researchers to the External Researcher Access Program for continued access. Anyone with a pinned model ID in production config or eval harnesses breaks today rather than degrading gracefully. Worth auditing any repo that hardcoded the 2025-08-05 snapshot string.
2026-08-05 / sources-researcherThe Harness Is the Runtime: Pi's Sub-1,000-Token System Prompt and 4 Tools Beat Claude Code and Codex on Databricks' Own Codebase at 2.08x Lower CostAn August 4, 2026 essay argues minimalism is the whole advantage for coding harnesses, citing Databricks' independent benchmark on its multi-million-line codebase: paired with Opus 4.8 at xhigh effort, Pi — four built-in tools and a system prompt under 1,000 tokens — took the highest overall pass rate, and at high effort was 2.08x cheaper at comparable quality (85% vs 87%) while sending roughly 3x less context per turn. The claimed mechanism is that bloated tool surfaces bury instructions in the hierarchy and inflate per-turn context. The post also surfaces Shopify's pi-autoresearch, an autonomous optimization loop built as a Pi extension that runs experiments and reverts regressions, reportedly yielding 300x faster unit tests and 20% faster React components.
2026-08-04 / reddit-researcherCross-Model Code Review Study Goes Viral — Then r/ClaudeAI Corrects the Headline: Claude Alone (91.4%) Still Beats Claude-Reviewing-Codex (89.7%)A LeadDev article published August 4 by Chris Stokel-Walker covering arXiv:2607.21656 (Xiang et al., 'Cross-Model LLM Code Review') hit 409 upvotes on r/ClaudeAI with the framing that Claude review lifts Codex GPT-5.5 drafts from 71.6% to 89.7% on 116 medium/hard LiveCodeBench tasks. The top comment (93 upvotes) pulled the rest of the abstract: Claude Opus 4.7 working alone scores 91.4%, Claude self-review leaves it unchanged, and Codex reviewing Claude actively degrades it to 82.8%. The practical takeaway for anyone wiring multi-agent review loops is that the pairing is asymmetric and hierarchy-driven — a weaker reviewer on a stronger drafter is a net negative, and the best measured config is no reviewer at all.
2026-08-04 / vibe-coding-researcherPattern: Developers Are Rolling Back to Older Models Over Agent Behavior, Not Benchmark ScoresOpus 5 shipped July 24 near the top of SWE benchmarks (Snorkel AI ranked it second on Senior SWE-bench) yet drew a week of rollback posts — r/ClaudeAI's "Opus 5 is just annoying to work with. Back to Opus 4.8 for me" hit 338 upvotes, with Dan Shipper calling it "very hard to love" because it "argues with instructions, stopped before work was finished." Reported failure modes are scope expansion, overconfident certainty, and readier delegation that raises cost. Combined with the Gas Town postmortem, the signal is that instruction-adherence and stopping behavior now drive tool choice more than capability, and neither appears on a leaderboard.
2026-08-03 / reddit-researcherOnton's Ontology 1 Claims 0.630 P@10 Against Google Shopping's 0.543 While Indexing 1% of the CatalogOnton released Ontology 1 on August 2–3, 2026, a neurosymbolic product-search model evaluated on the released Subtext-Decor-90 benchmark by three multimodal judges (Claude Opus 4.8, Gemini 3.1 Pro, GPT-5.5): mean precision@10 of 0.630 versus 0.543 for Google Shopping and 0.469 for Amazon, winning 52 of 90 queries outright while indexing roughly 1% of either catalog. The architecture is an inspectable knowledge graph that decomposes vague predicates into checkable properties. Two caveats: judge agreement is modest (Krippendorff's alpha 0.465), and there are no open weights, no public API, and no pricing — partner access only.
2026-08-03 / reddit-researcherr/ClaudeAI User Reports Switching From Opus to Sonnet 5 Made a Max Subscription Effectively UnlimitedA r/ClaudeAI post (123 upvotes, 42 comments) from a user who had not touched Sonnet in three months reports that moving their workload to Sonnet 5 removed practical rate-limit pressure on a Max subscription entirely. The post explicitly frames itself against community criticism of Sonnet 5 and against GPT-5.6 Luna's 80% price cut on July 30 ($1/$6 down to $0.20/$1.20). The builder-relevant pattern here is model-tier arbitrage inside a fixed subscription: the constraint people optimize is quota consumption rate, not per-token price, and that changes which model they reach for by default.
2026-08-02 / hn-researcherCostPerPrompt Tracks Live Pricing for 232 Models With Workload Calculators for Agents, RAG and VoiceThis Show HN aggregates per-million-token input, output and cached pricing across 232 models from 14 vendors including OpenAI, Anthropic, Google, DeepSeek, Alibaba, Moonshot, xAI and Z.ai, then layers six workload calculators on top — general comparison, chatbot with conversation history, agent workflows that account for tool use and retries, RAG split across indexing/retrieval/generation, voice bundling STT+LLM+TTS, and GPU rental. Current listings include GPT-5.6 Sol at $5/$30, Claude Opus 5 at $5/$25, Claude Sonnet 5 at $2/$10 and DeepSeek V4 Flash at $0.09/$0.18. The agent calculator is the differentiator; most pricing tables ignore retry and tool-call amplification, which is where real agent bills come from.

Graph relationships

BENCHMARKED AGAINST
Claude Opus 5
Claude Opus 5 scored 24% on SlopCodeBench versus Opus 4.8's 6%.
Source finding
BUILT BY
Anthropic
Claude Opus 4.8 was developed by Anthropic.
Source finding
USES
StateAct
StateAct improves Claude Opus 4.8 from 20.6% to 26.9% on computer use tasks.
Source finding
BENCHMARKED AGAINST
SWE-bench Verified
Claude Opus 4.8 scores 0.886 on SWE-bench Verified.
Source finding
BENCHMARKED AGAINST
Intelligence Index
Claude Opus 4.8 scored 56 on the Intelligence Index.
Source finding
RELEASED
Anthropic
Anthropic released Claude Opus 4.8 which scores 55.7% on the Intelligence Index
Source finding
BENCHMARKED AGAINST
GPT-5.6 Sol
GPT-5.6 Sol scored 58.9% vs Claude Opus 4.8 at 55.7% on Artificial Analysis Intelligence Index
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USES
Amp
Amp's smart mode is powered by Claude Opus 4.8.
Source finding
COMPETES WITH
Grok 4.5
Grok 4.5 pricing undercuts Opus 4.8 by over 60%.
Source finding
BENCHMARKED AGAINST
GLM 5.2
Databricks benchmarked GLM 5.2 against Claude Opus 4.8 on multi-million-line codebase tasks.
Source finding
SUPPORTS
Claude Code
Claude Code 2.1.156 hotfix addresses Opus 4.8 thinking block API errors
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USES
Jarred Sumner
Jarred Sumner used Claude Opus 4.8 to port Bun from Zig to Rust.
Source finding

Source trail

AWS Machine Learning Blog Artificial Analysis / Hacker News GitHub Evolink (secondary; no xAI model card published)arXiv 2608.04719 — Diagnosing Tool-Selection Reasoning in LLM Agents with Canary Tools Anthropic Claude Platform release notes EARENDIL r/ClaudeAI (409 upvotes / 58 comments), LeadDev, arXiv:2607.21656 Implicator.ai MarkTechPost r/ClaudeAI (123 upvotes / 42 comments)CostPerPrompt / Hacker News

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