I'll assemble tonight's Intelligence Radar brief for 1 October 2026 (Europe/Berlin) from primary lab, benchmark, and regulator sources.Cross-checking primary lab pages and the current Artificial Analysis board so prices and index versions stay unmixed.Tonight’s Intelligence Radar brief for Thursday, 1 October 2026 (Europe/Berlin). Weather of the frontier: a price-compressed three-lab cluster, with Google back on the independent board only behind a cyber-defender gate.

## 1. Date and weather

1 October 2026. The last ten days compressed the paid frontier toward a $2 / $10 per million token band, while independent scores still separate long-horizon agent work from cheap high-volume tiers. No single model is best. Board and harness matter.

## 2. Frontier and markets

Confirmed, 30 September: Google DeepMind announced Gemini 4 Argon, the first new Gemini frontier class since Gemini 3.1 Pro. Initial access is limited to trusted cyber defenders in the Fairwind Program, not general API. Introductory price is $2 input / $10 output per million tokens, cached input at 95% off ($0.10). Context is 1,048,576 tokens; published output budget is up to about 1 million tokens, from a prior ~64K. Google’s own card claims state of the art on DeepSWE v1.1 (77.9%) and the Vals Index (knowledge work weighted by U.S. GDP share), and a tie with GPT-6 Astra on CWE-bench v1 at 68%. On Terminal-Bench 4.0 Google reports Argon at 57.4%, behind Claude Opus 5.5 at 66.4% and GPT-6 Astra at 58.2%. Vendor numbers, not an independent rank.

Confirmed, 29 September: OpenAI released GPT-6.1 Sol (API id gpt-6.1-sol) at DevDay, priced like GPT-6 Sol at $2 / $10, with cache reads cut again. OpenAI says it nearly matches GPT-6 Astra on agentic coding, computer use, and professional work at about one-fifth of Astra’s standard token price. Available in ChatGPT Work, Codex, and the API.

Confirmed, 28 September: Anthropic shipped Claude Sonnet 5.5 (claude-sonnet-5-5) at the Sonnet 5 card, $2 / $10, with output reported more than 30% faster.

Confirmed, 22 September: Claude Opus 5.5 (claude-opus-5-5) at $4 / $20, 20% below Opus 5 list, cache reads $0.20 (about 60% below Opus 5). Anthropic says typical billed workloads run about 40% cheaper than Opus 5, and that the model is near Fable 5.1 on most work. Fast mode is $8 / $40. US-only inference is 1.1×. Same day, OpenAI shipped GPT-6 Sol ($2 / $10) and GPT-6 Luna ($0.10 / $0.50).

Confirmed, 21 September: xAI shipped Grok 4.7 (grok-4.7), 500k context, listed around $2 / $6, with configurable reasoning effort. Parameter counts circulating in secondary write-ups are not on a model card reviewed here; treat size claims as reported, not confirmed.

Reported, 1 October: Unbiased Pareto 26.10 Preview appears on release trackers. No primary card reviewed; do not re-label the atlas on it.

Artificial Analysis Intelligence Index must not be mixed across versions. On the v4.3.2 snapshot reported 1 October, Claude Opus 5.5 leads (about 58), Claude Sonnet 5.5 is next (about 56), and Gemini 4 Argon ties GPT-6 Astra (max) and Claude Fable 5.1 (max, with fallback) near 53, with GPT-6.1 Sol (max) about 52. Argon’s cost per Index task at the discounted rate is reported near $1.99 versus about $3.26 for Astra (max), roughly 60% of Astra’s cost. A BenchLeader mirror dated 29 September shows Opus 5.5 (thinking) at 57.6 on its own composite; that is not the same number as v4.3.2. Earlier v4.2 and v4.3 scales are not comparable: Fable 5 read 60 in July and 49.7 on v4.3 with no model change. Terminal-Bench 2.1 is saturated for ranking (top cluster inside about 2 points, Cognition SWE-2 at 92.8% on a 1 October mirror). Current terminal harness is Terminal-Bench 4.0.

ARC Prize verified, 30 September: GPT-6.1 Sol on ARC-AGI-3 scores 52.7% at about $7,600 (standard harness) and 96.4% at about $4,400 (provider-adapter harness); ARC-AGI-2 is 94.2% at $0.25/task; ARC-AGI-1 is 98.5% at $0.06/task. ARC Prize says the v3 adapter score is comparable to GPT-6 Astra’s 99.9% at about 77% lower cost. GPT-6 Luna, verified 22 September, is 0.19% / 0.59% on ARC-AGI-3 and 59.3% on ARC-AGI-2. ARC-AGI-1 is not a ranker.

## 3. Science of intelligence

The measurement story this week is harness dependence, not a new theory of mind. ARC Prize’s split between the standard harness (notes between turns) and the provider-adapter harness (opaque reasoning preserved, compaction allowed) moves GPT-6.1 Sol from 52.7% to 96.4% on ARC-AGI-3. That is evidence that interactive abstraction is still entangled with test-time state and tool policy. Chollet’s public line remains that ARC-AGI-3 is the unsaturated probe; ARC-AGI-1 and, increasingly, ARC-AGI-2 at the paid frontier are ceiling-compressed.

Artificial Analysis’s own v4.3 notes (early September, still the live family) put 45% of index weight on evaluations with private tasks or answers, with category weights agents 30%, coding 20%, general 30%, scientific reasoning 20%, and Terminal-Bench moved from 2.1 to 4.0. A composite that rebases under a release wave is a measurement instrument, not a capability fact. Epoch AI’s public trackers, data updated 1 October, still describe the Effective Compute Index frontier advancing about 14 points per year since reasoning models, with a 90% interval of +12 to +17. That is a scaling description, not a cognitive model.

## 4. Engineering

Availability is the engineering event. Argon’s 1M-token output budget is a product constraint change for long agent traces, not a published architecture paper. Cache discounts (Argon 95% off; Opus 5.5 cache reads at $0.20) dominate cost per finished task once agents loop. Opus 5.5 fast mode at 2× price for up to 2.5× speed is an explicit latency SKU.

Epoch AI, 16 September update and 1 October data refresh: the data-center explorer now covers an estimated 44% of global AI compute across 86 sites, and about 53% of compute newly deployed in 2026. End-2025 stock was about 20.3 million H100-equivalents, extrapolated to 31.6 million by September 2026. Chip-stock growth is listed at 3.4× per year (doubling every 6.8 months). Largest known site is about 1.1 million H100-equivalents. Training compute for frontier language models is still tracked at about 5× per year since 2020. Chip performance per dollar is about 1.49× per year since 2023. Energy and siting, not parameter count, remain the binding inputs.

Cognition’s SWE-2 (10 September, reported base Kimi K3) leads saturated Terminal-Bench 2.1 mirrors. That is a coding-agent product signal, not a general-intelligence rank.

## 5. Political, legal, social

Confirmed in official and law-firm readings of Regulation (EU) 2026/1744: the Digital Omnibus entered into force 27 July 2026 and postponed Annex III high-risk obligations to 2 December 2027, and high-risk systems embedded in regulated products to 2 August 2028. Transparency duties for chatbots and AI-altered content began 2 August 2026, enforced by the AI Office for GPAI and prohibited practices, and by national authorities otherwise. A new prohibition on non-consensual intimate synthetic imagery applies from 2 December 2026. Fines cited for GPAI breaches reach the higher of €15 million or 3% of worldwide turnover; prohibited-practice exposure is higher, up to €35 million or 7%. Reported, not re-verified tonight: the AI Office opened early investigations in 2026 into hiring, credit, and student-monitoring systems.

Argon’s Fairwind-only rollout is an availability restriction framed as cyber defense. It is a de facto export of capability by program membership, not a published statute. Amodei’s September call to slow capability release (reported via Reuters alongside the Opus 5.5 launch) is a lab-chief statement, not a binding pause: Opus 5.5, Sonnet 5.5, and peers shipped anyway. Anthropic says Opus 5.5 was externally tested by Frontier Design and METR and was about 85% less likely than Opus 5 or Mythos 5.1 to attempt containment bypass in an internal eval. That figure is vendor-reported.

## 6. Watchlist hits

- Gemini 4 Argon blog and model card: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/ and https://deepmind.google/models/gemini/ — confirmed, gated.
- Claude Opus 5.5 pricing: https://www.anthropic.com/claude/opus — confirmed.
- ARC Prize GPT-6.1 Sol card: https://arcprize.org/results/openai-gpt-6-1-sol and https://arcprize.org/leaderboard — confirmed, harness-split.
- Artificial Analysis v4.3 family (do not mix with v4.2): https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v4-2 is the prior rebase; Argon tie is reported on v4.3.2 mirrors dated 1 October, not yet treated as a new AA article in this brief.
- Epoch data centers: https://epoch.ai/latest/scaling-ai-data-centers-research — confirmed update.
- EU text path: Regulation (EU) 2026/1744; Commission note on 2 August transparency start, IP/26/1714.

## 7. Ledger actions

Frontier label, task-conditional only: on AA Intelligence Index v4.3.2, Opus 5.5 (thinking / max) is the current composite lead; Argon joins Astra and Fable 5.1 in the tie band but is not generally available, so it does not displace a public Frontier default until Fairwind opens. On Terminal-Bench 4.0 vendor cards, Opus 5.5 leads the named set; on DeepSWE v1.1 and Vals, Argon leads Google’s card. Efficient: GPT-6.1 Sol and Sonnet 5.5 at $2 / $10, if independent cost-per-task holds near Astra quality. Budget: GPT-6 Luna at $0.10 / $0.50, explicitly not Frontier on ARC-AGI-3. Five-benchmark atlas: drop Terminal-Bench 2.1 and ARC-AGI-1 as rankers; keep Terminal-Bench 4.0, ARC-AGI-3 with harness named, AA Index version pinned, plus one private-task professional set (AA-Briefcase or Vals) and one cyber set (CWE-bench) only with the access regime stated. A public Argon API listing, an AA article that rebases to v5, or a Luna-class model clearing 20% on ARC-AGI-3 standard harness would move labels.

## 8. Sources

https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/
https://deepmind.google/models/gemini/
https://www.anthropic.com/claude/opus
https://arcprize.org/leaderboard
https://arcprize.org/results/openai-gpt-6-1-sol
https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v4-2
https://epoch.ai/latest/scaling-ai-data-centers-research
https://epoch.ai/
https://ec.europa.eu/commission/presscorner/api/files/document/print/en/ip_26_1714/IP_26_1714_EN.pdf

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