Text Embedding 3 Large
OpenAI text embedding model producing 3,072-dimensional vector representations across an 8,192-token context window. It scores 64.6 on MTEB and 54.9 on MIRACL for search, clustering, and retrieval systems.
OpenAI
OpenAI
Specifications
Context window, ranked against other embedding models
Proportional scale: 0 to 8.2K tokens.
Benchmarks & Performance Rankings
Empirical intelligence benchmarks and category leaderboard placements for Text Embedding 3 Large.
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p99: —ms
—tok/s
SWE-bench: 0%
Benchmarks
Pricing
Rates are read live
Pricing for text-embedding-3-large is fetched from the live catalogue on load, so it is never served from a cache that could outlive a repricing.
Availability
Not enough data yet
We have not collected enough health probes for this model to publish an uptime or latency figure. A percentage from a handful of samples is fabricated precision, so none is shown until the sample count supports one.
How Text Embedding 3 Large is billed
Billed at the provider's list price, with no per-token markup.
- Exact list price
- Tokens settle at the published rate of the model that served your call.
- Cache discounts passed through
- Provider prompt-caching discounts reach your balance with no added fee.
- Cost on every response
- Each response carries the
x-nr-request-costheader, so you can reconcile spend per request.