# Liquid d1 > d1 is Liquid AI's decision model family. It answers typed yes or no, choice and score questions about text and images with probabilities, through a hosted API and the open-weight d1-3B and d1-omni-600M models. - Canonical: https://www.anchorterminal.com/tools/liquid-d1 - Markdown: https://www.anchorterminal.com/tools/liquid-d1.md (~7,600 tokens) - Slim: https://www.anchorterminal.com/tools/liquid-d1.min.md (~1,480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/tools/liquid-d1.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - Updated: 2026-10-08 ## Overview **Grade E · 43.5/100 · rank #582 of 629 · #8 in Decision models · not agent-ready · confidence medium** ## Assessment The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found. The family launched between 22 September and 7 October 2026. ## Facts | Field | Value | | --- | --- | | Vendor | Liquid AI (https://www.liquid.ai) | | Kind | Model API | | Category | Decision models (https://www.anchorterminal.com/categories/decision-models) | | Transport | HTTP | | Endpoint | `https://api.liquid.ai/decisions/v1/systemone` | | Auth | API key · A key created at console.liquid.ai under Dashboard, API Keys, after registering and joining an organisation, sent as a Bearer header. Keys start with `liquid_`. No scopes, expiry or rotation were found in the reviewed documentation. The weights download from Hugging Face without an account. | | Pricing | Freemium (Freemium) · The hosted `d1` model costs $0.04 per million input tokens and bills no output tokens, per the launch post of 5 October 2026 (https://www.liquid.ai/blog/d1-decision-model). Each question is billed as its own prompt, and an image counts 1.5 tokens per 32 by 32 pixel patch. A text-only `d1:free` model exists, with no published limits. Liquid's pricing page covers model licensing only. The open weights are free to run, and commercial use is free below $10 million in annual revenue. | | x402 | No · No x402, MPP or L402 in the d1 docs, the launch posts or the terms of service (checked 2026-10-08). | | Licence | The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published | | Source | https://huggingface.co/LiquidAI/d1-3B | | Docs | https://docs.liquid.ai/lfm/models/decision-models | | llms.txt | https://docs.liquid.ai/llms.txt | | Last release | 2026-10-07 | | Models | Hosted `d1` (text and images) and `d1:free` (text only). Open weights d1-3B (3.12B parameters, from LFM2.5-VL-3B, text and images) and d1-omni-600M (587M, text with images or audio, described as experimental) | | Question types | noul, choice and score (2 to 10 levels), several a request, in the request shape of TypeSafe's System One API | | Input | State as text or JSON, plus up to 8 JPEG, PNG, WebP or GIF images as Base64 on the hosted `d1`. JSON body under 4.5 MB and at most 10,000 image patches a request | | Context | 32,768 tokens for d1-3B and 16K for d1-omni-600M per Liquid's docs. OpenRouter and Vercel list 65,536 for the hosted d1. Liquid's own docs give no figure for the hosted model | | Free tier | `d1:free`, text only. No limits published | | Trains on API data | Yes. The terms of 30 September 2026 allow training and fine-tuning on submitted content and outputs | | Rate limits | Not found in the reviewed documentation | | Weights | LFM Open Licence v1.0 on Hugging Face, ungated, loaded with `trust_remote_code=True` on transformers 5.14 or later. GGUF builds for llama.cpp, whose server answers `/v1/systemone` | | Licence | Commercial use of the weights is free below $10 million in annual revenue. Above it a paid licence from Liquid is needed. Qualified non-profits are exempt for research and non-commercial use | | Gateways | OpenRouter (`liquid/d1`) and Vercel AI Gateway, each at $0.04 per million input tokens | | Capabilities | inference.decision | | Tags | hosted, model, open-weights, source-available, self-hosted, llms-txt, free-tier, usage-priced | | JSON | https://www.anchorterminal.com/api/v1/tools/liquid-d1.json | ## Score breakdown (methodology v0.4, October 2026 research run) Assessed 2026-10-08 from public evidence against the published checklist (https://www.anchorterminal.com/benchmark/#checklist). Confidence: medium. Performance and Task success pending (no score, not in the total); the total is Σ(score × weight) ÷ 80 over the 7 assessed categories. "This run" is each category's share of the 100 points. | Category | Weight | This run | Score (0–100) | Points | | --- | --- | --- | --- | --- | | Reliability | 16% | 20 | 21 | 4.2 | | Performance | 10% | pending | pending | n/a | | Schema & documentation | 13% | 16.2 | 59 | 9.6 | | Agent ergonomics | 13% | 16.2 | 63 | 10.2 | | Security & auth | 14% | 17.5 | 35 | 6.1 | | Payments & pricing | 10% | 12.5 | 27 | 3.4 | | Task success | 10% | pending | pending | n/a | | Maintenance & community | 7% | 8.8 | 60 | 5.2 | | Transparency & trust (editorial 46, provenance 62) | 7% | 8.8 | 54 | 4.7 | | Negative events | up to −15 | up to −15 | none recorded | 0 | | **Total** | | | | **43.5 → E** | ### Why each score - Reliability 21: Scored as a hosted model API, the surface an outside agent would call, with the open weights noted. No status page is linked from the site, the docs or the launch posts, and status.liquid.ai did not answer our reader (0). With no page there is no incident history to read, and the hosted model has been public since 22 September 2026 per the API's own model list (5 of 30). No request or token rate limits found. The docs give image limits only, 8 images and a 4.5 MB body (0 of 15). Liquid documents no 429 or overload handling. A decision has no side effects, so a retry is safe, and TypeSafe's SDKs, the documented clients, retry 408, 429 and 5xx with backoff per the Jev listing's check of 1 October (6 of 15). No SLA for the API. The pricing page mentions SLAs only for enterprise licence customers (0). The `d1` model carries no beta or preview label, though it followed an experimental release by about a week (10). - Performance: Pending. Latency is measured per call by our probes, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until the first probe window closes. - Schema & documentation 59: No OpenAPI file found. api.liquid.ai/openapi.json and two docs paths returned 404. The API follows TypeSafe's System One request, `GET /decisions/v1/models` answers without a key, and llama.cpp's server README specifies the same request for local runs (10 of 25). llms.txt, llms-full.txt and a Markdown twin of every docs page (10). The docs say what d1 is for and list the tasks that need a language model instead. No limitations or failure-mode page (15 of 20). Three question kinds behind a `type` field, 2 to 10 score levels, and a table of image limits. The hosted limits on questions, options and state size aren't stated (11 of 15). curl, Python and TypeScript examples with full responses for every question type. One error message is documented, for images sent to `d1:free`, and no status codes (9 of 15). Model IDs are `d1` and `d1:free` with no version, and no API changelog was found. The weights have commit history on Hugging Face (4 of 15). - Agent ergonomics 63: Read as an API an agent calls for a decision, as with Jev and Clef. Answers are a few numbers a question and no output tokens are produced. Each question is billed as its own prompt, with the state and every image counted again, and no caching or batch endpoint was found for the hosted API (16 of 25). The caller fixes the output shape, with several questions and up to 8 images a request (17 of 20). No error codes or bodies documented beyond one message (5 of 20). Calls are stateless and safe to retry, and Liquid's agent skill file says to treat HTTP errors as failures and keep a bounded retry policy. No retry guidance of Liquid's own (14 of 20). `instructions` and `criteria` are the only question fields, and TypeSafe's Python and TypeScript SDKs work by changing the base URL. They don't send images, so image calls need raw HTTP (11 of 15). - Security & auth 35: Read for a model API. A bearer key from console.liquid.ai, tied to an organisation. No scopes, expiry or rotation found, and revocation is unchecked because the console needs a login (17 of 30). The terms of 30 September 2026 allow Liquid to use submitted content and outputs for training and fine-tuning, and retention is 'as reasonably necessary'. No opt-out or zero-retention option found. Running d1-3B locally keeps data on your hardware (5 of 20). The terms say results are estimates and call for human review of significant decisions, and the skill file says an approval verdict doesn't replace authorisation checks. Nothing covers hostile or injected content in the state. Local use loads custom code with `trust_remote_code=True`, and we found no network or shell calls in the four files we read (5 of 15). Responses report input tokens, and the terms say organisation administrators can see usage. No request logs documented (4 of 15). No security.txt, disclosure policy or bug bounty found, and the terms forbid vulnerability testing without written authorisation. The Vanta trust centre is unread (4 of 20). - Payments & pricing 27: No x402, MPP or L402 (0). The launch post states $0.04 per million input tokens with no output tokens, readable without a login, and the docs give the image token formula. The price sits in a blog post and on gateway pages, not on Liquid's pricing page (15 of 20). A text-only `d1:free` model is on the API's public model list and in the docs' examples. Its limits aren't published and we couldn't check whether the console asks for a card (12 of 20). A person registers at the console and joins an organisation to create a key. The weights download without an account, but other open-weight listings with a hosted route get no onboarding credit for that (0). - Task success: Pending. Task success needs the category task suites run through each tool, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until then. A data provider's data-quality score is published on its listing now and becomes half of this category when it's scored. - Maintenance & community 60: Read for a model. The open weights were released on 7 October 2026 and the hosted d1 with vision on 5 October (30). The deprecations page lists retired open models with replacements and no notice periods, and the terms let Liquid change or discontinue any model without obligation (4 of 12). The hosted model went from an experimental release to `d1` with vision in about two weeks under unversioned IDs, too short a record to show churn (4 of 8). No API changelog. Support is a Discord server, and six of eight Hugging Face discussions on d1-3B were merged within days, with replies on the two open ones (8 of 15). No SDK of its own. TypeSafe's SDKs (Python 0.7.2 of 26 September, npm 0.6.0) are the documented clients (8 of 15). The d1-3B repository has three commits on main and custom model code, with GGUF builds and upstream llama.cpp support (6 of 10). - Transparency & trust 54: The hosted model is closed under clear terms. The weights and model code are public under the LFM Open Licence v1.0, which is Apache-2.0 with a $10 million revenue limit on commercial use, so not an OSI licence. A plain-language guide explains it, and training code and data aren't published (20 of 30). The terms and the privacy policy, both dated 30 September 2026, agree that content may be used for training. Neither gives a retention period, and no DPA was found. The site's FAQ still says Liquid has no hosted API of its own (14 of 30). A deprecations page for open models without dates, and no policy for the hosted API (6 of 20). The privacy policy says services are hosted in the United States and names Google Analytics and PostHog. No subprocessor list found, and the trust centre is unread (6 of 20). Fix list for a coding agent, everything this grade says the listing lacks, the biggest gain first (27 items): https://www.anchorterminal.com/fixes/liquid-d1.md (JSON https://www.anchorterminal.com/fixes/liquid-d1.json) ### What we couldn't check - unchecked: whether status.liquid.ai exists. Our reader's connection to it failed, and no status page is linked from the site or docs - unchecked: the trust centre at trust.liquid.ai, which renders only with JavaScript, so certifications and any subprocessor list are unread - unchecked: the console at console.liquid.ai, which needs a login, so key revocation, usage logs, spending limits and whether a card is needed are unread - unchecked: Liquid's GitHub organisation (Liquid4All). GitHub's API refused our reader with a rate limit - unchecked: hybrid.py and lfm2_vl.py in the d1-3B repository. We read api.py, runner.py, prompt.py and modeling_d1.py - The limits of `d1:free` and the rate limits of `d1`. Neither is published - The hosted context window. OpenRouter and Vercel list 65,536 tokens, and Liquid's docs give 32,768 for d1-3B and no figure for the hosted model - Whether the hosted `d1` is d1-3B. Liquid's pages don't say - Which path TypeSafe's SDKs reach. The curl examples post to /decisions/v1/systemone, and the SDK examples set only the base URL https://api.liquid.ai - The first release date. The API's model list gives `d1:free` a release date of 22 September 2026, OpenRouter says 1 October, and the launch post of 5 October refers to an experimental release the week before - Whether Vercel AI Gateway accepts images. Its model list tags d1 with vision, and the launch post says the gateways are text only for now - The model card links https://www.liquid.ai/blog/open-d1, which returns 404. The post is at https://www.liquid.ai/blog/d1-open, and a Hugging Face discussion of 8 October reports the wrong link - The site's FAQ says Liquid doesn't offer a hosted API of its own, which the launch post and the terms contradict - Liquid's benchmark, latency and cost comparisons are its own, and we didn't reproduce them ### Sources - launch post for the hosted d1, with price and methodology: (seen 2026-10-08) - launch post for the open weights: (seen 2026-10-08) - decision models overview: (seen 2026-10-08) - hosted d1 API page: (seen 2026-10-08) - d1-3B docs page: (seen 2026-10-08) - d1-omni-600M docs page: (seen 2026-10-08) - decision model guide: (seen 2026-10-08) - agent skill file: (seen 2026-10-08) - docs llms.txt: (seen 2026-10-08) - deprecations page: (seen 2026-10-08) - licence guide: (seen 2026-10-08) - public model list on the API: (seen 2026-10-08) - d1-3B model card: (seen 2026-10-08) - d1-3B licence text: (seen 2026-10-08) - d1-3B repository metadata, commits and discussions: (seen 2026-10-08) - d1-3B GGUF card: (seen 2026-10-08) - llama.cpp server README, /v1/systemone: (seen 2026-10-08) - terms of service: (seen 2026-10-08) - privacy policy: (seen 2026-10-08) - pricing page: (seen 2026-10-08) - site FAQ: (seen 2026-10-08) - OpenRouter listing: (seen 2026-10-08) - Vercel AI Gateway model list: (seen 2026-10-08) - typesafe-sdk on PyPI: (seen 2026-10-08) - @typesafe-ai/sdk on npm: (seen 2026-10-08) - RDAP record for liquid.ai: (seen 2026-10-08) ## Who's behind it (provenance 62/100, checked 2026-10-08) | Check | Finding | Points | | --- | --- | --- | | Legal entity named | Liquid AI, Inc. | 20/20 | | Domain age | liquid.ai, registered 2017-12-16 (8 years) | 11/15 | | Endpoint on the vendor's domain | api.liquid.ai | 15/15 | | Terms of service | read, states 7 of the 7 things a reader expects, and has 1 clause that costs points | 8/10 | | Privacy policy | read, states 8 of the 8 things a reader expects, and has 1 clause that costs points | 8/10 | | Status page | not found | 0/10 | | Changelog | not found | 0/10 | | security.txt | not found | 0/10 | The terms of service (updated 30 September 2026) name Liquid AI, Inc., a Delaware corporation, and Massachusetts law. The privacy policy carries the same date. RDAP gives liquid.ai a registration date of 16 December 2017 and a transfer on 20 April 2023. The site footer says the company was established in 2023. The hosted endpoint is on api.liquid.ai. The weights sit on huggingface.co under the LiquidAI organisation. /.well-known/security.txt returned 404 on www.liquid.ai, liquid.ai and api.liquid.ai. No status page is linked from the site, the docs or the launch posts, and status.liquid.ai did not answer our reader. No changelog for the API or the docs was found. docs.liquid.ai/changelog returned 404. A trust centre at trust.liquid.ai is hosted by Vanta and renders only with JavaScript, so its contents are unread. ### Terms and privacy, as read A reading by a fixed set of rules, each answered with the vendor's own sentence. Not legal advice. **Terms of service** (https://www.liquid.ai/terms-conditions), read 2026-10-08, dated 2026-09-30, states 7 of the 7 things a reader expects. - To know. Says it may use customer content to train or improve models, and no opt-out was found (costs points). "You also grant Liquid AI and its affiliates a worldwide, non-exclusive, royalty-free license to use Your Content to develop and improve Liquid AI’s models, products, and services, including through training, fine-tuning, evaluation, and testing." - Gives the date it was last updated. Last updated 2026-09-30. - Names the governing law or courts. The law of the Commonwealth of Massachusetts. - States a limit on its liability. Capped at the greater of US$100 and the fees paid in the 12 months before the claim. - Says how changes to the terms are announced. Changes are posted, with no other notice named. - Also in the text (2026-10-08). The customer may not use the services or outputs to develop, train, fine-tune or improve other AI models. "use the Services or outputs to develop, train, fine-tune, or improve other AI models;" - Also in the text (2026-10-08). The customer is responsible for all activity and charges on its account or credentials, including those incurred by automated systems. "You are responsible for all activity and charges incurred through your account or credentials, including by automated systems and authorized third-party applications." - Also in the text (2026-10-08). On termination the right to use the services ends and customer content may be deleted or become inaccessible. "Upon termination, your right to use the Services ends. You remain responsible for Fees incurred before termination, and Your Content may be deleted or become inaccessible." **Privacy policy** (https://www.liquid.ai/privacy-policy), read 2026-10-08, dated 2026-09-30, states 8 of the 8 things a reader expects. - To know. Says it may use customer content to train or improve models, and no opt-out was found (costs points). "Training, fine-tuning or otherwise enhancing AI models and related technologies using inputs and outputs you share, and Personal Data that may be incidentally included in our training datasets" - To know. Says it sells personal data or shares it for advertising. "We sell and/or share your Personal Data, subject to your right to opt-out as described in this section." - Gives the date it was last updated. Last updated 2026-09-30. - Says how long data is kept. For as long as needed, with no period named. - Says whether personal data is sold or shared for advertising. Says it does not sell personal data. - Gives a privacy contact. legal@liquid.ai. - Says where data is transferred or stored. Relies on standard contractual clauses. - Also in the text (2026-10-08). The policy names an objection to personal data being used to train models, listed under rights for residents of the EEA, Switzerland and the UK. "For example, you can object to your Personal Data being used to train our AI models." - Also in the text (2026-10-08). Session replay through PostHog may record clicks, mouse movements and keystrokes or text entered into forms on the services. "Session replay technology may collect information about your interactions with the Services, such as pages viewed, clicks, scrolling, mouse movements, keystrokes or text entered into forms, device and browser information, and other usage information." ## Live (updated 2026-10-08 17:36 UTC) - Right now: up, HTTP 404, 157 ms, checked 2026-10-08 17:36 UTC (get on `https://api.liquid.ai/decisions/v1/systemone`) - Uptime 24h 100.0% (25 probes) · 30 days 100.0% (25 probes) · p50 164 ms · p95 278 ms - security.txt: none - Always current: https://www.anchorterminal.com/api/v1/live/liquid-d1.json ## Probe metrics Not measured yet. Our benchmark probes haven't run, so there's no availability, latency or error rate from a run and Performance is pending. Live uptime, where we poll the endpoint, is under Live and doesn't change the score. ## Prices | Item | Price | Unit | Note | | --- | --- | --- | --- | | d1 input | $0.04 | per 1M tokens | No output tokens. Each question is billed as its own prompt, images at 1.5 tokens per 32 by 32 pixel patch | Across all listings: https://www.anchorterminal.com/prices/index.md ## Strengths - $0.04 per million input tokens with no output tokens billed, per the launch post, and a text-only `d1:free` model - d1-3B (3.12B parameters, 32,768-token context) and d1-omni-600M are ungated on Hugging Face, with GGUF builds - llama.cpp's server README documents `/v1/systemone` for d1, so the same request runs locally - The hosted `d1` model accepts up to 8 images a request as Base64 data - Docs are served as Markdown with an llms.txt index, and say when to use a language model instead ## Weaknesses - The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found - No status page, rate limits, SLA or error reference found for the hosted API - The LFM Open Licence v1.0 ends free commercial use at $10 million in annual revenue, so the weights aren't open source - No OpenAPI file, API changelog or versioned model IDs. The hosted models are `d1` and `d1:free` - No SDK of its own. TypeSafe's SDKs are the documented clients and don't send images ## Before you call it (notes for agents) 1. POST to https://api.liquid.ai/decisions/v1/systemone with a `liquid_` key as a Bearer header. This is not a chat-completions endpoint 2. Use `d1` for images. `d1:free` is text-only and answers that it does not accept images 3. Send images as Base64 data URLs in `images`, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused 4. Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again 5. Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data ## Connect Install: ```bash pip install typesafe-sdk # or: npm install @typesafe-ai/sdk ``` First request: ```bash curl -s https://api.liquid.ai/decisions/v1/systemone \ -H "Authorization: Bearer $LIQUID_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"d1","state":"I have been waiting over three weeks for my order and nobody has responded to my emails.","questions":{"is_complaint":{"type":"noul","instructions":"Is this message a complaint from the customer?"}}}' ``` ## Similar tools Ranked by shared capabilities, then score. Same-category tools with no shared capability key are listed last. | Tool | Grade | Score | Rank | Shared capabilities | x402 | Markdown | | --- | --- | --- | --- | --- | --- | --- | | OpenAI Decisions API | BB | 71.5 | 102 | inference.decision | no | https://www.anchorterminal.com/tools/openai-decisions-api.md | | Laya | B | 69.2 | 153 | inference.decision | no | https://www.anchorterminal.com/tools/convai-laya.md | | Kev | B | 67.4 | 194 | inference.decision | no | https://www.anchorterminal.com/tools/jaredpalmer-kev.md | | Vela 2.0 | B | 66.5 | 219 | inference.decision | no | https://www.anchorterminal.com/tools/vela.md | | Clef | B | 66.1 | 224 | inference.decision | no | https://www.anchorterminal.com/tools/cloudflare-clef.md | | Jev | B | 62.1 | 309 | inference.decision | no | https://www.anchorterminal.com/tools/typesafe-jev.md | ## Panel reviews (0) Reviewed by the Anchor panel (https://www.anchorterminal.com/reviewers/index.md): . Desk reviews, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. For a desk review, the outcome says whether the reviewer's questions could be answered from public material: success, partial or failure. How reviews work: https://www.anchorterminal.com/reviews/how-it-works.md ## Notable - Liquid's docs tell callers to use TypeSafe's SDKs (`typesafe-sdk`, `@typesafe-ai/sdk`) with the base URL https://api.liquid.ai, and say those SDKs don't support images yet (source: ) - The terms of service, updated 30 September 2026, grant Liquid a licence to use submitted content and outputs to develop and improve its models, including through training (source: ) - Liquid says d1-3B scores 48.57 on the Decision Index 0.2.1, from its own run of the official scorer and not a leaderboard submission. This is Liquid's number, not ours (source: ) - Liquid reports 8 ms a decision for d1-3B on an NVIDIA RTX 4090 and 30 ms on an Apple M5 Pro, and 200 to 300 ms for a text decision on the hosted API. These are Liquid's numbers, not ours (source: ) - llama.cpp's server README documents `POST /v1/systemone` and names lfm2-d1 and lfm2-d1-omni among the models it serves, with up to 255 options for a choice question (source: ) - d1 is also listed on OpenRouter and Vercel AI Gateway at $0.04 per million input tokens with a 65,536-token context. The launch post says both are text only for now (source: ) - On 8 October 2026 the Hugging Face API showed 5,370 downloads and 139 likes for LiquidAI/d1-3B, whose repository was created on 5 October (source: ) ## Compare - [Clef vs Liquid d1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.md): B 66.1 vs E 43.5 - [Laya vs Liquid d1](https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md): B 69.2 vs E 43.5 - [Kev vs Liquid d1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.md): B 67.4 vs E 43.5 - [Liquid d1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.md): E 43.5 vs BB 71.5 - [Liquid d1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.md): E 43.5 vs C 61.3 - [Liquid d1 vs Jev](https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev.md): E 43.5 vs B 62.1 - [Liquid d1 vs Vela 2.0](https://www.anchorterminal.com/compare/liquid-d1-vs-vela.md): E 43.5 vs B 66.5 ## Verify this listing For the vendor. The badge or a plain link to this page verifies the listing, from a page on liquid.ai or one of its subdomains. It shows the listing is the vendor's and that the vendor knows it's here, and it never changes a grade, rank or review. The vendor sends the page's address to `POST https://www.anchorterminal.com/api/v1/verify` as `{"slug": "liquid-d1", "url": "…"}`, or calls the `verify_listing` tool at https://www.anchorterminal.com/mcp. We fetch the page once, then again every week; two failed checks in a row and the verification lapses, and a later pass restores it. What we check: https://www.anchorterminal.com/builders/index.md#verify HTML badge: ```html Liquid d1 on Anchor Terminal ``` Markdown badge, for a README: ```markdown [![Liquid d1 on Anchor Terminal](https://www.anchorterminal.com/badges/liquid-d1.svg)](https://www.anchorterminal.com/tools/liquid-d1) ``` Plain link: ```html Liquid d1 on Anchor Terminal ``` ## Share this listing For the vendor. Sharing assets for social media, two PNGs of 1200 × 630 that say Liquid d1 is listed on Anchor Terminal, with the vendor's logo and this page's address and no grade or score. - Dark: https://www.anchorterminal.com/assets/share/liquid-d1-dark.png - Light: https://www.anchorterminal.com/assets/share/liquid-d1-light.png