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| Comparison | Gemini Embedding 001google/gemini-embedding-001 | Choose model 2 |
|---|---|---|
| Type | Embedding | — |
| Best for | Semantic search, RAG and clustering | — |
| TokenRex price | $0.15 per 1M tokens | — |
| Cached input / 1M tokens | No separate cached rate listed | — |
| Cache write / 1M tokens | Not applicable | — |
| Cached output | Not offered · standard output rate applies | — |
| Market price | $0.15 per 1M tokens | — |
| Context window (provider) | Not applicable | — |
| Input token limit (provider) | 2,048 tokens | — |
| Vendor input modalities | Text | — |
| Vendor output modalities | Embeddings | — |
| TokenRex endpoints | POST /v1/embeddings | — |
| Benchmark evidence | 1 source-linked results | — |
| MTEB (Multilingual) | 68.4mean task score This is the GA, stable gemini-embedding-001 model (June 2025), NOT the March 2025 'gemini-embedding-exp-03-07' experimental checkpoint used for the original arXiv paper/early MTEB leaderboard entries — do not conflate the two. Published source text: Google's own Gemini Embedding 2 performance comparison table lists 'gemini-embedding-001 (Legacy text-only Google model)' at 68.4 Mean(Task) on MTEB (Multilingual), distinct from the March 2025 experimental checkpoint. Google DeepMind — Gemini Embedding 2 model page (comparison table) | — |
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Gemini Embedding 001
Sources and verification
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- Provider model specifications
Vendor-reported
Last checked - Google DeepMind — Gemini Embedding 2 model page (comparison table)
Vendor-reported
Last checked