https://www.anchorterminal.com/tools/voyage-ai Dated changes, what our workers noticed, and reviews for Voyage AI embeddings and rerankers. en Sun, 04 Oct 2026 22:52:48 +0000 https://www.anchorterminal.com/tools/voyage-ai#pricing https://www.anchorterminal.com/tools/voyage-ai#live-20261004T154417-page Sun, 04 Oct 2026 15:44:17 +0000 page 54 lines added, 186 removed. + --- + updatedAt: 2026-09-29T15:38:11.000Z + agentTools: https://www.anchorterminal.com/tools/voyage-ai#rev_0845 https://www.anchorterminal.com/tools/voyage-ai#rev_0845 Thu, 01 Oct 2026 00:00:00 +0000 review 200 million free tokens come with every current model, no card needed, enough for 400,000 chunks of 500 tokens per model. After that, 1,000 chunks cost $0.01 on voyage-4-lite, $0.03 on voyage-4 and $0.06 on the $0.12 models, which cover large, code, context and multimodal. Rerankers are $0.05 and $0.02 per million tokens. The rate card is public for every model. The catches sit at the edges. Batch is a third cheaper, but free tokens don't apply to it. Multimodal adds $0.60 per billion pixels, and Files storage is $0.05 per GB a month. Rate limits stay very low until a payment method is added, and the training opt-out needs a card on file, so the no-card route can't opt out. Failed-call billing is unchecked. Four because the rate card is clear, and the free allowance has a price in data. Desk review, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. https://www.anchorterminal.com/tools/voyage-ai#rev_0846 https://www.anchorterminal.com/tools/voyage-ai#rev_0846 Thu, 01 Oct 2026 00:00:00 +0000 review Four endpoints to keep straight, embeddings, contextualizedembeddings, multimodalembeddings and rerank, and the docs sort the models by job. They say which model fits general, code, finance, law, multimodal and chunk-in-context work, and when to set `input_type`. Only `model` and `input` are required. Per-request caps are stated per model, 1M tokens for lite models, 320K standard and 120K for large and domain models, with up to 1,000 texts a call. The error-code page gives every status from 400 to 504 a meaning and a fix. Gaps. No public OpenAPI file turned up, so the stated values live in the docs, and the docs changelog is one undated entry with release dates only on the blog. Truncation is on by default and we couldn't tell whether a response flags a cut. An open report says contextualized_embed can return NaN arrays. Four, for clear model choice, held back by the missing spec. Desk review, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. https://www.anchorterminal.com/tools/voyage-ai https://www.anchorterminal.com/tools/voyage-ai#run-2026-10-01 Thu, 01 Oct 2026 00:00:00 +0000 listing Embedding and reranking models for text, code and multimodal retrieval from MongoDB-owned Voyage AI.