**Intelligence Radar DAILY BRIEF**  
**11 October 2026 (Europe/Berlin)**  

Frontier weather: Anthropic’s Claude Opus 5.5 leads Artificial Analysis Intelligence Index v4.3.2 at 58 (max effort), while price cuts and the new Haiku 5.5 widen the efficient/budget tiers; Gemini 4 Argon remains restricted; measurement continues to emphasize private agentic sets and scaffolding over raw model jumps.

### Frontier & markets
Claude Opus 5.5 (Anthropic, 22 September, confirmed) holds the top of Artificial Analysis Intelligence Index v4.3.2 at 58 (max with fallback), leading on six of the ten constituent evaluations including Humanity’s Last Exam (61.4%), SciCode (66.9%), AA-Briefcase v1.1 (Elo 1822), GDPval-AA v2.1, AA-Omniscience, and AutomationBench-AA. Terminal-Bench 4.0 is level with the prior leader. Pricing is $4/$20 per million input/output tokens (20% cut from Opus 5) with cache reads at $0.20. Four of five effort levels sit on the intelligence-vs-cost-per-task Pareto frontier. Claude Sonnet 5.5 (28 September) scores ~56 and is available at $2/$10; Anthropic halved its cache-read price to $0.10 on 7 October, lowering typical agentic cost ~20%.

Claude Haiku 5.5 (7 October, confirmed primary) is the first Haiku in a year: $0.10/$0.50 per million tokens for prompts ≤100k (90% of prior Haiku traffic), rising to $0.50/$2.50 above that; 1M context, 128k output, adaptive thinking with effort controls. Anthropic reports strong gains versus Haiku 4.5 on OSWorld 2.1 offline (72.4% vs 15.7%), Terminal-Bench 4.0 (39.2% vs 0%), and knowledge-work Elos; Artificial Analysis lists it at ~43 on v4.3.2. It is positioned for high-volume sub-agent, classification, and latency-sensitive work and is available on the Claude Platform and major clouds.

GPT-6.1 Sol (OpenAI, 29 September, confirmed) keeps the $2/$10 price of GPT-6 Sol while cutting cached input to $0.10 (95% discount). OpenAI positions it as near-Astra on agentic coding, computer use, and professional work at roughly one-fifth the token price; Artificial Analysis scores it ~52 on v4.3.2. GPT-6 Astra (3 September) remains the higher-priced flagship (~53, $10/$50). GPT-6 (Sol/Luna) is rolling to ChatGPT Free and Go tiers with Intelligent UI features. Mistral Large 4 Preview (6 October, reported) scores ~38 on the same index and is the leading Western open model so far; open weights are promised by month-end. Gemini 4 Argon (Google DeepMind, 30 September, confirmed limited) is available only to Fairwind Program cyber defenders at introductory $2/$10 (later $4/$20), with 1M output tokens; Google reports leading scores on DeepSWE v1.1 (77.9%) and several knowledge-work suites. Artificial Analysis Intelligence Index v4.3.2 incorporates ten evaluations (AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity’s Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1) with increased private-set weighting; v5 is targeted for late October. Saturated exams are not used as rankers. No single model is declared best absent a specific task and harness.

### Science of intelligence
Epoch AI’s InnovationEval (7 October, confirmed) tasked frontier models with inventing a novel post-training advance comparable to a recent human technique (on-policy self-distillation). After corrections for selective reporting and scope, Claude Fable 5 captured ~2% and GPT-5.6 Sol ~15% of the target improvement; outputs largely rediscovered prior literature or gamed runs. Contaminated later models still failed full independent replication. Epoch’s Capabilities Index continues to advance ~14 points per year since reasoning models; the cost of a fixed performance level has fallen ~47% per quarter since 2023. Automation Reports (8 October) show Fable 5.1 and GPT-6 Astra ~65% on real Epoch research tasks, reliable on well-defined coding/computation but weaker on judgment, style, and open-ended design. ARC Prize ARC-AGI-3 remains far from saturation on standard harnesses (GPT-6 Astra ~62.7% verified max, no-tools); community and Kaggle scaffolding (notably Tufa Labs frameworks) have produced substantially higher public scores, illustrating that agent scaffolding and search can dominate raw model upgrades on novel interactive environments. The $700k human-level prize remains unclaimed. Measurement emphasis continues to shift toward private held-out agentic knowledge work and multi-step workflows rather than saturated academic exams.

### Engineering
Agent systems remain the practical frontier. Terminal-Bench 4.0 and OSWorld variants show strong results for Claude Sonnet/Opus 5.5 and open models such as Qwen3.8 Max on some computer-use boards (~86% reported on certain OSWorld aggregates). Adaptive thinking and effort parameters are now standard on recent Claude and GPT models, enabling explicit cost–quality trade-offs. Epoch projects that HBM shipments through 2027 could support tens to hundreds of millions of concurrent frontier-model agents (or billions of efficient open models), equating to working hours of hundreds of millions of knowledge workers if run continuously. Cache-price reductions (Anthropic Sonnet, OpenAI Sol) are first-class availability events that materially lower multi-turn agent costs. Restricted access (Gemini 4 Argon Fairwind, certain cyber variants) continues to segment capability by user class.

### Political / legal / social
EU AI Act GPAI obligations, Article 50 transparency, and Commission enforcement have been active since 2 August 2026; high-risk system deadlines were deferred by the Digital Omnibus (Regulation (EU) 2026/1744) to 2 December 2027 (Annex III) and 2 August 2028 (Annex I). The US continues without a comprehensive federal statute; policy relies on executive orders, voluntary industry pledges (including a September White House accord on audits and board oversight), and a state patchwork (California frontier transparency, New York RAISE Act reporting, Colorado reenacted consequential-decision rules effective 2027). Transatlantic divergence remains policy, not lag: the US emphasizes light-touch approaches at G20 while the EU proceeds with enforcement and has signaled continued interest in international safety monitoring. Content-marking grace periods end 2 December 2026 for systems already on the market.

### Watchlist hits (primary)
- Anthropic Claude Haiku 5.5 announcement and system card: https://www.anthropic.com/claude-haiku-5-5  
- Artificial Analysis on Opus 5.5 and Index methodology: https://artificialanalysis.ai/articles/claude-opus-5-5 and https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index  
- Epoch InnovationEval and Automation Reports: https://epoch.ai/publications/innovationeval and https://epoch.ai/publications/can-ai-automate-epoch  
- Google DeepMind Gemini 4 Argon: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/  
- ARC Prize results and leaderboard: https://arcprize.org/results  

### Ledger actions
Haiku 5.5 at $0.10/$0.50 (≤100k) and the Sonnet cache cut would re-label the Budget and Efficient tiers on cost-sensitive agentic and high-volume tasks; Opus 5.5’s 58 on v4.3.2 (with its Pareto position) updates the Frontier board for agentic knowledge work and Terminal-Bench 4.0 under the named harness. Gemini 4 Argon remains off the general Frontier board pending broader availability. ARC-AGI-3 scaffolding gains argue for explicit harness decomposition in the five-benchmark atlas rather than pure model ranking. Any Index v5 rebase will require full re-evaluation of Frontier/Efficient/Budget cutoffs. Availability pauses or region blocks remain first-class events.

**Sources**  
https://www.anthropic.com/claude-haiku-5-5  
https://artificialanalysis.ai/articles/claude-opus-5-5  
https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index  
https://epoch.ai/publications/innovationeval  
https://epoch.ai/publications/can-ai-automate-epoch  
https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/  
https://arcprize.org/results  
https://openai.com/index/introducing-gpt-6-1-sol/  

Ask Intelligence Radar a task for a Task Router ticket (5 benchmarks → Frontier / Efficient / Budget + optional decomposition).