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Inference · memory estimate
Gemini Embedding 001
Closed weights. No supported local deployment or GPU requirement is published.
API cost
USD / month
Standard text-token estimate. Excludes taxes, caching, batch discounts, reasoning and multimodal surcharges. Provider limits and regional availability may differ.
Gemini Embedding 001
Capabilities
Context window
2,048 tokens
Maximum input
2,048 tokens*
Maximum output
1 tokens
Reasoning
No
Tool calling
No
Open weights
No
Knowledge cutoff
2025-05
API mode
Embeddings*
Input modalities
text
Output modalities
text
System configuration
Detailed specifications
Specifications · 9 fields
deprecation date
2028-05-20*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
input cost per token
1.5e-7*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
input cost per token batches
1.2e-7*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
litellm provider
vertex_ai-embedding-models*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
max input tokens
2,048*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
max tokens
2,048*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
mode
embedding*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
output cost per token
0*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
output vector size
3,072*Scope and conditions
native_context
provider
vertex_ai-embedding-models*
mode
embedding*
full_native_model_id
gemini-embedding-001*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*