text-embedding-004 on Google Vertex AI

Released
2023-02-01
Last refreshed
2026-06-15
Status
Researched 166d ago
ProprietaryCommercial use: restricted
Google DeepMind releases · 51 in the last 12 months · this family litChangelog →
Specifications
Released
2023-02-01
Context
2K
Architecture
Decoder Only
Specialization
general
Openness
Proprietary
License
ProprietaryRestricted
Weights
Not released
Code
Unknown
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
-
Input / 1M
$0.100

Cheapest of 1 route · GCP Vertex AI

Providers(1)

About

text-embedding-004 on Google Vertex AI is Google DeepMind's Gemini Embedding model. It was released 2023-02-01.

Providers(1)

Compare API pricing across 1 tracked provider route for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
GCP Vertex AI$0.100-
ServerlessPartial

Available via routers & gateways(13)

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
69.53MTEB(eng, v2)Observed 2026-10-17
Harness: mteb 2.26.6 leaderboard aggregation, Mean (Task) over 41 tasks
Evaluator: MTEB (embeddings-benchmark/results)
Confidence: confirmed
Notes: MTEB(eng, v2) Mean (Task) 69.53 over 41 tasks; Mean (TaskType) 64.82. Computed with the leaderboard's own code (mteb 2.26.6 Benchmark summary table) from embeddings-benchmark/results @ 4bb41dd (2026-10-17). Source: MTEB (embeddings-benchmark/results, CC0). Retrieved 2026-10-17.

Migration checks

No linked migration route is available for this model yet.