SeaLink
Embeddings API gateway (Singapore) — Gemini Embedding models, USD pricing, no chat completions
SeaLink is a Singapore-based embeddings API gateway providing access to Gemini Embedding 001 and Gemini Embedding 2. Pricing is in USD per 1M input tokens with no output charge. SeaLink does not offer chat completions — it is an embeddings-only service. Billing is in USD.
Embeddings-only API gateway in Singapore — Gemini Embedding 001 ($0.135/1M) and Gemini Embedding 2 ($0.18/1M) with USD billing and no output charge.
- Gemini Embedding 001 and Gemini Embedding 2 at competitive USD rates
- Singapore-based — low latency for Southeast Asia workloads
- Simple USD billing with no output charge for embeddings
- Embeddings only — no chat completions or other modalities
- Small catalog limited to Gemini Embedding models
- Newer provider with limited public track record
SeaLink Models
| Model | Modality | Tier | Price | Cached /1M | TTFT | Throughput | Context | Intel. | Caps | |
|---|---|---|---|---|---|---|---|---|---|---|
Gemini Embedding 001 Gemini Embedding | Embedding | budget | $0.14/ $0.00 in / out per 1M EST Oct 2026 | — | — | — | 2K | — | ||
Gemini Embedding 2 Gemini Embedding | Embedding | efficient | $0.18/ $0.00 in / out per 1M EST Oct 2026 | — | — | — | 2K | — |
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SeaLink is an inference API provider that hosts open-weight and third-party large language models. SeaLink is a Singapore-based embeddings API gateway providing access to Gemini Embedding 001 and Gemini Embedding 2. Pricing is in USD per 1M input tokens with no output charge. SeaLink does not offer chat completions — it is an embeddings-only service. Billing is in USD. Common use cases include Embeddings, Semantic search, RAG, Vector databases. Headquartered in Singapore, founded 2024. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
SeaLink vs other LLM providers
SeaLink competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. Embeddings-only API gateway in Singapore — Gemini Embedding 001 ($0.135/1M) and Gemini Embedding 2 ($0.18/1M) with USD billing and no output charge. Use the LLM provider comparison tool to see SeaLink token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose SeaLink?
SeaLink stands out because: Embeddings-only API gateway in Singapore — Gemini Embedding 001 ($0.135/1M) and Gemini Embedding 2 ($0.18/1M) with USD billing and no output charge.. The API currently offers 2 models, spanning 1 efficient, 1 budget tiers. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding SeaLink token pricing
SeaLink charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. Prices shown are sourced from SeaLink's public pricing page and updated every 15 minutes. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
SeaLink context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. SeaLink's largest context window is 2K tokens. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when SeaLink makes sense
Managed inference APIs like SeaLink eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at SeaLink API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical SeaLink token price data is available in the LLM price history charts.
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