Capabilities
7-day heat trend
+6.5%Pricing breakdown
Typical 3:1 output-to-input mix, per 1M tokens
Estimated monthly cost by workload
Market position
- Cheaper than 43% of tracked models
- Faster than 29% of tracked models
- Efficiency rank: #791 of 1105
Best suited for
Code generation, refactoring and review, and developer-tooling workloads with large context.
About embed-code
Relace Embed Code embeds code snippets for vector search and semantic retrieval workflows.
embed-code is a Code model from Relace (US). HotON.ai tracks it at $0.00 per 1M input tokens and $0.00 per 1M output tokens, with a 1K-token context window, ~137 tokens/sec throughput and 98.6% availability. Its composite efficiency score is 88/100 at an estimated $0.000 per successful task.
Compare embed-code
Related market news
Frequently asked questions
How much does embed-code cost per 1M tokens?+
embed-code is tracked at $0.00 per 1M input tokens and $0.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.00 per 1M tokens. Figures are illustrative demo data.
What is embed-code best for?+
Code generation, refactoring and review, and developer-tooling workloads with large context.
How fast is embed-code?+
embed-code delivers about 137 tokens/sec with 98.6% tracked availability, suitable for latency-sensitive, real-time applications.
Is embed-code cheaper than other AI models?+
Within the HotON.ai tracked set, embed-code is cheaper than 43% of models on input price and ranks #791 of 1105 by overall efficiency.
Related models
Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Speed, availability and efficiency are modeled estimates.