d1-ultra released
Liquid AI · Model release
Source confirmed
Data as of October 15, 2026 · How the score is built
CurrentProprietaryNon-Reasoning
d1-ultra
Decision readingd1-ultra is tracked, but not publicly ranked yet. The profile exposes 0 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Released Oct 15, 2026 — see all recent releases
d1-ultra will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Decision-system
Radar
Full release historyd1-ultra release history
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Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- d1-ultraLiquid AI d1-ultra launch
- Context window
- Not publishedLiquid AI d1-ultra launch
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageLiquid AI d1-ultra launch
- Output modalities
- typed JSONLiquid AI d1-ultra launch
- Parameters
- Not disclosed by the provider
- Availability
- Liquid API · Liquid ConsoleLiquid AI d1-ultra launch
- Cloud regions
- Not tracked yet
- Lifecycle
- activeLiquid AI d1-ultra launch
- API capabilities
- POST /decisions/v1/systemone with model d1-ultra. Text, images, or both as state, plus one or more Noul (yes/no probability), Choice (one label from many), or Score (position on a scale) questions, answered in one forward pass with no generated tokens. Billed on input tokens only; each question is billed as its own prompt.Liquid AI d1-ultra launch
- Prompt caching
- Not documented in the pricing recordLiquid AI d1-ultra launch post
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track d1-ultra, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.
d1-ultra is a proprietary model. No explicit reasoning mode is documented in this profile.
Hosted on the Liquid API as model d1-ultra, through the System One decisions endpoint, with text, image, or text-and-image state. Liquid lists Vercel and OpenRouter as coming soon. No open weights, parameter count, or context limit are published. Images count as 1.5 input tokens per 32x32-pixel patch, so a 1024x1024 image is 1,536 tokens, and each question is billed as its own prompt.
Liquid AI released d1-ultra on October 15, 2026, as a hosted decision model on the Liquid API at $0.042 per million input tokens, billed on input only. It takes text, images, or both and returns Noul, Choice, or Score answers in one forward pass without generating tokens. Liquid says it is built on a larger open-weight model than d1 with Liquid-specific customization, and it names no base model, parameter count, context limit, or downloadable weights. Its independent Decision Index v1.0 results sit on the benchmark page and stay separate from Decision Index 0.2.1, Decision Index 0.3, JevBench, and general model rankings. Liquid's own 112-evaluation comparison with d1 and Jev 1.14 is a provider-run suite without published tasks, so those figures stay in the source review and not on a benchmark page.
The profile has no source-displayable benchmark row yet.
Last updated October 15, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does d1-ultra perform overall in AI benchmarks?
d1-ultra does not have any source-displayable benchmark rows yet, so this profile does not assign a public score or rank. Documented specifications remain visible, while score-led charts and claims stay unavailable until a published evaluation can be attached to the exact model.
Does d1-ultra have full benchmark coverage on BenchLM?
No. d1-ultra currently has 6 source-displayable rows across 680 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of d1-ultra?
d1-ultra's provider has not published a context-window limit for this exact model. The profile leaves the value unavailable instead of borrowing a number from an earlier family member or a third-party route. Maximum output length is tracked separately when the provider documents it.