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TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
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`CodeRankEmbed` is a 137M bi-encoder supporting 8192 context length for code retrieval. It significantly outperforms various open-source and proprietary code embedding models on various code retrieval tasks. Check out our blog post and paper for more details! Combine `CodeRankEmbed` with our re-ranker `CodeRankLLM` for even higher quality code retrieval.

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CodeRankLLM

nomic-ai

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COST EXPLORER

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Cost analysis

Adjust monthly token usage to compare estimated API costs.

1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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Selection guide & FAQ
How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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