The state of the AI frontier, in one place

By raw input price, GPT-5.4 nano (OpenAI) is lowest at $0.20 per 1M input tokens. But real workloads pay for output too — the cheapest to actually run, on a blended $/1M at a 3:1 input:output mix, is Llama 4 Maverick at $0.38 per 1M. Open-weights models can also be self-hosted for the cost of your own hardware.

GPT-5.5 leads at 1.05M tokens. It's not alone at the top: 13 of the 19 models tracked have a 1M-class (~1,000K-token) window, so very-long-context work is no longer a single-vendor feature.

At the ~1M-token frontier, yes: the cheapest open-weights model, Llama 4 Maverick, runs about 4.1× cheaper than the cheapest proprietary one, Grok 4.3, on a blended $/1M at a 3:1 input:output mix ($0.38 vs $1.56 per 1M). Open weights also self-host for hardware cost alone — the trade-off is that you run the infrastructure and the top proprietary models still lead on some frontier reasoning tasks.

Every figure is hand-verified against each provider's own published pricing and cross-checked for contradictions. Each row carries its own verification date and a link to the provider's official pricing page (both shown in the full table below). The catalog was last updated 20 Jul 2026, and the last full cross-provider sweep was 20 Jul 2026; newer arrivals are verified on their own dates. It's a single, versioned source of truth (version 2026-07-20) that every BitByteCore tool reads, so a price can't drift between pages. Model pricing moves fast, so confirm with the provider before you rely on a figure.

Yes. The full catalog is published as machine-readable JSON at https://bitbytecore.com/data/frontier.json and as schema.org Dataset markup on this page. Quote or cite it with clear attribution and a link back.