**13 October 2026, Europe/Berlin.** Gemini 4 Argon moves to general developer and subscriber availability while Meta’s Muse Wonder series posts its first frontier agent scores; Claude Opus 5.5 still leads Artificial Analysis Intelligence Index v4.3.2.

### Frontier & markets
Google DeepMind made Gemini 4 Argon generally available today via the Gemini API (AI Studio / platform), Google AI Ultra in Antigravity, and Pro/Ultra subscribers in the Gemini app and AI Mode. Introductory API pricing is $2 per million input tokens and $10 per million output tokens (cached input at 95% discount / $0.10); rates double after 30 November. Output limit is 1 million tokens. Lab claims include SOTA on DeepSWE v1.1 (77.9%) and #1 on the Vals Index for economic-sector knowledge work (finance, coding, legal, tax). Early limited access was restricted to Fairwind cyber defenders from 30 September.

Meta released Muse Wonder and Muse Wonder Full on 12 October as its first frontier-class models, trained at the Prometheus gigawatt-scale data center. Features include Active Memory (cross-conversation context retention) and Active Focus (goal persistence, error recovery, clarification). Muse Wonder is available via Meta Model API and Muse Code at $4 / $20 per million input/output tokens (cached input $0.20); Muse Wonder Full is limited to Muse Code subscribers. Context is 1M tokens (text/image/video/audio in, text out). Meta claims agentic and coding wins, including on DeepSWE and SWE-Marathon in third-party runs; independent AA Intelligence Index v4.3.2 lists Muse Wonder Full (max) at 55.8, just behind Claude Sonnet 5.5 (max) at 56 and Opus 5.5 (max) at 57.6.

Anthropic’s Claude Haiku 5.5 (7 October) prices at $0.10 / $0.50 per million tokens for prompts ≤100k (matching GPT-6 Luna), rising to $0.50 / $2.50 above that threshold, with cache reads at $0.01 / $0.05. Anthropic estimates ~75% lower average run cost versus Haiku 4.5 after tokenizer effects. Sonnet 5.5 cache-read prices were halved. Mistral Large 4 (1T total / ~49–52B active parameters, multimodal) entered public API preview on 6 October (~$1.36 / $4.18, with promotional rates reported); open weights are promised by end of October. On AA Index v4.3.2 it scores 38.4.

Current AA Intelligence Index v4.3.2 (as of 13 October) tops with Claude Opus 5.5 (max) 57.6, Sonnet 5.5 (max) 56, Muse Wonder Full (max) 55.8, GPT-6 Astra (max) ~52.7, Gemini 4 Argon (high) ~52.6. Do not mix versions; earlier v4.3 snapshots differ. Saturated static exams are not primary rankers. No single best model exists without a task and harness.

### Science of intelligence
François Chollet (ARC Prize) argued on 7–8 October that the “jagged frontier” is concentrated in verifiable domains (math and code) that can be pushed arbitrarily far with RLVR, while non-verifiable areas remain bottlenecked by human-generated data and show slower gains. He notes that domain practice (programming, mathematics) improves domain skill but does not raise general skill-acquisition efficiency—the definition of intelligence in his 2019 measure paper.

A Neuron review (7 October, Summerfield et al.) discusses the “recipe” for intelligence in natural and artificial systems: how components (architectures, cost functions, algorithms) fit together, with parallels between biological and foundation-model systems. A companion NeuroView outlines steps toward an automated science of the mind (experiment representation, synthetic behavior, model synthesis, closed-loop theory discovery). Tenenbaum’s recent work continues to emphasize probabilistic programs and Bayesian models of cognition integrated with language models rather than treating LLMs as end-to-end intelligence.

ARC-AGI-3 (interactive) community high score reached 68.91% by Tufa Labs on 13 October (up from ~56%), reclaiming first place; earlier milestones used open scaffolds (e.g., small open LLMs + Python REPL). Verified model scores remain lower on standard harnesses.

### Engineering
Gemini 4 Argon’s 1M output token limit and long-horizon DeepSWE performance target multi-step coding, research, and cyber workflows. Meta’s Active Memory / Active Focus aim at persistent personal and professional agents (insurance claims, leases, app building). Terminal-Bench 4.0 and OSWorld-Verified remain active agentic harnesses; SWE-bench Verified shows Claude Fable 5 near 95% in some reports. Inference economics are shifting via cache discounts and effort controls (Haiku 5.5 first Haiku with adjustable effort). Energy notes are sparse beyond Meta’s gigawatt-scale training claim; no major chip or inference-system primary updates today.

### Political / legal / social
EU AI Act: Digital Omnibus (Regulation (EU) 2026/1744, in force 27 July) delayed Annex III high-risk obligations to 2 December 2027 and Annex I to 2 August 2028. Article 50 transparency duties (chatbot disclosure, synthetic content marking) have applied since 2 August 2026; machine-readable marking for pre-existing generative systems and new bans on non-consensual intimate imagery / CSAM generation apply from 2 December 2026. Fines remain up to €35M / 7% global turnover for prohibited practices. US White House Accord (29 September) commits major labs to internal controls, external scrutiny, and board oversight for frontier models, overlapping EU GPAI systemic-risk duties.

### Watchlist hits with primary links
- Gemini 4 Argon GA: https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/ (confirmed).
- Muse Wonder announcement: https://about.fb.com/news/2026/10/introducing-muse-wonder-models/ and https://research.meta.ai/blog/muse-wonder (confirmed).
- AA Index v4.3.2 leaderboard snapshots: artificialanalysis.ai (confirmed rankings as of 13 Oct).
- ARC Prize ARC-AGI-3 high-score post: https://x.com/arcprize (13 Oct, confirmed).
- Chollet jagged-frontier posts and Neuron papers (reported / primary journals).

### Ledger actions
New entries warranted for Gemini 4 Argon (post-GA independent results) and Muse Wonder / Wonder Full on AA Index v4.3.2 and agentic boards (Terminal-Bench 4.0, OSWorld-Verified, DeepSWE). Haiku 5.5 and Mistral Large 4 preview affect Efficient / Budget labels via price and open-weight status. Track Mistral weights drop for open atlas updates. No re-base of saturated static exams. Five-benchmark atlas remains task-specific; Frontier / Efficient / Budget labels require per-task evidence.

### Sources
https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/  
https://about.fb.com/news/2026/10/introducing-muse-wonder-models/  
https://research.meta.ai/blog/muse-wonder  
https://www.anthropic.com/claude-haiku-5-5  
https://artificialanalysis.ai  
https://arcprize.org  
https://www.cell.com/neuron/fulltext/S0896-6273(26)00643-4  
https://digital-strategy.ec.europa.eu/en/news/ai-omnibus-enters-force  

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