Gemini Embedding 001
tempr/google/gemini-embedding-001 · family gemini · in: text → out: text · price provider-declared (via models.dev). Capabilities: text.
$0.11
Blended $/1M (3:1)
$0.15
Input $/1M
free
Output $/1M
$0.15
1M in + 1M out
—
Cache read $/1M
#1000 of 7,513
Cheapest rank
- Provider
- Tempr (
tempr) - Kind
- text (outputs text)
- Context
- 2,048 tokens
- Max output
- 1 tokens
- Capabilities
- text
Same model, other providers
“Gemini Embedding 001” is offered by 6 providers — cheapest-effective first. This one (Tempr) is the cheapest.
| Provider | Input | Output | Blended | Context |
|---|---|---|---|---|
| Tempr (this) | $0.15 | free | $0.11 | 2k |
| Vertex | $0.15 | free | $0.11 | 2k |
| $0.15 | free | $0.11 | 2k | |
| Merge Gateway | $0.15 | free | $0.11 | 2k |
| SAP AI Core | — | — | — | 2k |
| Vercel AI Gateway | — | — | — | 8k |
Call it
jishie indexes & prices models; it does not proxy inference.
Most providers are OpenAI-compatible — point base_url at Tempr and pass this model id:
curl $BASE_URL/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" -H "Content-Type: application/json" \
-d '{"model":"google/gemini-embedding-001","messages":[{"role":"user","content":"hello"}]}'
Route programmatically with MCP find_model / get_model, or fetch this record free (no wallet):