liquid
LiquidAI: d1-ultra
liquid/d1-ultra
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to its OpenRouter catalog listing, d1-ultra is described as Liquid AI's largest decision model, served as a System One endpoint. It accepts text and image inputs together with typed questions and returns a decision output rather than free-form text. The catalog reports a 32,768-token context length. No independent model card was available in this source pack, and the listing provides no benchmark results, so all capabilities should be treated as catalog-reported and validated against your own workload before adoption.[1]
Strengths
- The OpenRouter catalog describes d1-ultra as Liquid AI's largest decision model, positioned for structured choice-making rather than general text generation.[1]
- The catalog declares both text and image input modalities, allowing a decision request to combine written state with visual context.[1]
- The listing reports a 32,768-token context length, which is substantial for catalog-described decision inputs.[1]
Limitations
- Output is restricted to decisions; the catalog lists no free-text or other output modalities.[1]
- The only evidence is the OpenRouter catalog; no independent model card was available in this source pack, so reported capabilities remain unverified.[1]
- The catalog shows no benchmark results and no declared reasoning support, leaving measured performance and knowledge cutoff unknown.[1]
Where to use it
Sources
- [1] OpenRouter catalog · LiquidAI: d1-ultraSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
d1-ultra is Liquid AI's largest decision model, served as a System One endpoint. Send a state of text and images along with typed questions, and it returns a choice, a...
Specifications
- Model ID
- liquid/d1-ultra
- Canonical ID
- liquid/d1-ultra-20261015
- Creator
- liquid
- Added to OpenRouter
- 15.10.2026
- Context length
- 32,768
- Modality
- text+image->decisions
- Input modalities
- text, image
- Output modalities
- decisions
- Token pricing
- No per-token price in the source snapshot — see OpenRouter for the billing unit
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Liquid | 32,768 | — | — | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.