Deepstory Research

The Frontier AI Model Race (2026)

Release cadence, capability-vs-cost frontier, benchmark trajectory, training compute, and the new axis of safety-gated capabilities.

Curated snapshot Last updated: Aug 5, 2026 21 data points
Model release timeline

Model release timeline

Quarterly frontier-model releases by lab, 2024 → 2026.

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Capability vs cost (frontier)

Capability vs cost (frontier)

Each point is a frontier model: y = benchmark score, x = $/M tokens.

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Benchmark trajectory by lab

Composite benchmark score over time, leading labs.

Placeholder — no source-verified values seeded yet
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Training compute growth

Training compute growth

Estimated training compute per frontier release (log scale, FLOPs).

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Safety-gated capabilities matrix

Safety-gated capabilities matrix

For each model × domain: allowed (green) / safety-gated (amber) / blocked (red).

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Data table

The Frontier AI Model Race (2026) — full data table
meta google openai series quarter anthropic source_ref value_basis model benchmark_score cost_per_m_tokens year flops_estimate bio chem cyber legal medical
0 0 1 releases 2024 Q2 1 anthropic-news Claude 3.5 Sonnet (Jun 2024); GPT-4o (May 2024) — Anthropic + OpenAI release notes
1 0 1 releases 2024 Q3 0 openai-research OpenAI o1-preview (Sep 2024); Meta Llama 3.1 405B (Jul 2024)
0 1 1 releases 2024 Q4 0 google-deepmind Google Gemini 2.0 (Dec 2024); OpenAI o1/o3 (Dec 2024)
0 0 0 releases 2025 Q1 1 anthropic-news Claude 3.7 Sonnet (Feb 2025)
1 0 0 releases 2025 Q2 1 meta-ai Meta Llama 4 (Apr 2025); Anthropic Claude 4 / Opus 4 (May 2025)

16 more rows + CSV download

The full 21-row dataset, one-click CSV export, and the AI-ready context file are free with an account. Prefer to verify it yourself? The full methodology and sources are published below.

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Methodology & sources

Last updated: Aug 5, 2026

Methodology

Source-backed values are seeded for four of the five charts: the release cadence by lab (2024 → 2026, from each lab’s release notes), the capability-vs-cost scatter (Artificial Analysis Intelligence Index vs output $/M tokens, June 2026 snapshot), training-compute growth by year (Epoch AI, corroborated by Stanford HAI), and a safety-gated capabilities matrix. Every numeric point carries a sources[].ref and a value_basis. Sources are each lab’s own model cards/release notes, Artificial Analysis, Epoch AI, and Stanford HAI — cross-checked against public release timelines. EDITORIAL ENCODING: the safety-gated matrix scores each model × domain as 3 = allowed / 2 = gated / 1 = blocked. This is an interpretation of each model’s published safety policy, not a measured benchmark. PLACEHOLDER: the per-lab benchmark-trajectory chart is left unseeded — a consistent historical per-quarter, per-lab benchmark series was not sourceable without mixing incompatible benchmarks. Re-verified 2026-06-15.

Comparisons are informative, not definitive. See each source for definitions and limits.

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