Text Embedding 3 Small vs Gemini Embedding 001
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| Comparison | Text Embedding 3 Smalltext-embedding-3-small | Gemini Embedding 001gemini-embedding-001 |
|---|---|---|
| Type | Embedding | Embedding |
| Best for | Semantic search, RAG and clustering | Semantic search, RAG and clustering |
| TokenRex price | $0.02 per 1M tokens | $0.15 per 1M tokens |
| Cached input / 1M tokens | No separate cached rate listed | No separate cached rate listed |
| Cache write / 1M tokens | Not applicable | Not applicable |
| Cached output | Not offered · standard output rate applies | Not offered · standard output rate applies |
| Web search | Not applicable | Not applicable |
| Market price | $0.02 per 1M tokens | $0.15 per 1M tokens |
| Context window (provider) | — | Not applicable |
| Input token limit (provider) | Within the context window | 2,048 tokens |
| Vendor input modalities | Text | Text |
| Vendor output modalities | Embeddings | Embeddings |
| TokenRex endpoints | POST /v1/embeddings | POST /v1/embeddings |
| Benchmarks | ||
| Benchmark evidence | 2 source-linked results | 1 source-linked results |
| MTEB (English average) | 62.3% OpenAI release evaluation, January 25, 2024. Published English embedding-task average; not a TokenRex run. Source: “the average score on a commonly used benchmark for English tasks (MTEB) has increased from 61.0% to 62.3%”. OpenAI · New embedding models and API updates | — |
| MIRACL (multilingual retrieval) | 44% OpenAI release evaluation, January 25, 2024. Published multilingual retrieval average; not a TokenRex run. Source: “the average score on a commonly used benchmark for multi-language retrieval (MIRACL) has increased from 31.4% to 44.0%”. OpenAI · New embedding models and API updates | — |
| 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) |
No overall score, winner or cost-versus-score frontier is calculated without comparable, attributable benchmark evidence. Different test configurations appear separately. Vendor capabilities are distinct from TokenRex API support.
— means no published value or no matching capability. Provider token limits are not tested gateway guarantees; TokenRex media controls and response formats are listed separately.
Text Embedding 3 Small
Sources and verification
Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.
- Vendor model documentation
Vendor-reported
Last checked - OpenAI · New embedding models and API updates
Vendor-reported
Last checked
Gemini Embedding 001
Sources and verification
Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.
- Provider model specifications
Vendor-reported
Last checked - Google DeepMind — Gemini Embedding 2 model page (comparison table)
Vendor-reported
Last checked
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