GTE Large EN v1.5

EmbeddingsUnavailable

by Communitygte-large-en-v1-5

Alibaba (Tongyi Lab) general text embedding model. The v1.5 release extends the context to 8192 tokens and returns 1024-dim vectors, scoring competitively on MTEB while handling much longer inputs than typical 512-token encoders. A practical open model when documents exceed the usual short-context limit.

See alternatives Compare

Status: Unavailable
Context: 8,192 tokens
Input → output: Text → Vector
Developer: Community
Updated: September 23, 2026

GTE Large EN v1.5 is currently unavailable

You can still read the details on this page. Pick one of the available alternatives below to run a comparable model right away.

Go to alternatives

Comparable models

All in this category

OpenAI text-embedding-3-largeOpenAI
OpenAI's highest-quality embedding model. Returns 3072-dim vectors by default and supports reducing dimensions via the dimensions parameter. Outperforms text-embedding-3-small and the older ada-002 on MTEB and multilingual MIRACL retrieval benchmarks, for cases where accuracy matters more than cost.
$0.156/1M in
Compare GTE Large EN v1.5 vs. OpenAI text-embedding-3-large
OpenAI text-embedding-3-smallOpenAI
OpenAI's small, low-cost embedding model. Returns 1536-dim vectors by default and supports shortening output dimensions via the dimensions parameter without retraining. Replaced text-embedding-ada-002 with better retrieval quality at a fraction of the price, and is the default choice for general-purpose semantic search and RAG.
$0.024/1M in
Compare GTE Large EN v1.5 vs. OpenAI text-embedding-3-small

Playground

Try GTE Large EN v1.5

Input & output

Currently unavailable

Currently unavailable.

The playground is disabled. You can find comparable models in the same category: Browse alternatives

Text

0 / 8,000

Text to embed (up to 8192 tokens)

Compare with (optional)

Runs the model twice (billed twice).

⌘/Ctrl + Enter

Output

The vector appears here.

This run

No price – currently unavailable.

New here?

10 free credits ($0.10) when you sign up with Google

Usable 24 hours after sign-up, up to 5 runs per day and at most 2 credits per run. Other sign-in methods start without credits.

About GTE Large EN v1.5

TL;DRAs of September 23, 2026

GTE Large EN v1.5 is a model by Community in the Embeddings category. GTE Large EN v1.5 is currently not available on Railwail. The context window holds 8,192 tokens.

gte-large-en-v1.5 from Alibaba's Institute for Intelligent Computing (Tongyi Lab) is a general text embedding model whose v1.5 update pushes the supported context to 8192 tokens, well beyond the 512-token ceiling of most BERT-based encoders. It outputs 1024-dim embeddings and posts competitive MTEB English scores, making it useful for long-passage retrieval and RAG over bigger chunks without aggressive splitting. It loads with trust_remote_code on Hugging Face and is served via the feature-extraction pipeline; mean-pool the token outputs for the sentence vector.

Pricing

Currently unavailable. There is no price for this model at the moment, so it cannot be run.

API

Call GTE Large EN v1.5 with your Railwail API key. Use this model ID in the request:

gte-large-en-v1-5API documentation Get an API key

Currently unavailable

The model has no verified price or is deactivated; API calls are refused.

Specifications

Model ID: gte-large-en-v1-5
Developer: Community
Category: Embeddings
Input: Text
Output: Vector
Context window: 8,192 tokens
Catalog entry updated: September 23, 2026

Input parameters

Inputs and settings from the model's input schema. The example in the API section shows which of them the API accepts.

ParameterTypeDefaultAllowed values

inputsrequired
Text to embed (up to 8192 tokens)
Type: Text
Default: –
Allowed values: up to 8,000 characters

Use cases

Related guides

Embedding Models for Search & Science

All models in Embeddings

Frequently asked questions

What is GTE Large EN v1.5?

GTE Large EN v1.5 is a model by Community in the Embeddings category. It is listed on Railwail but cannot be run at the moment.

How much does GTE Large EN v1.5 cost on Railwail?

GTE Large EN v1.5 cannot be run on Railwail at the moment, so there is no current price. Available alternatives with prices are listed further down this page.

What is the context window of GTE Large EN v1.5?

The context window of GTE Large EN v1.5 holds 8,192 tokens.

How fast is GTE Large EN v1.5?

There are not enough measured runs of GTE Large EN v1.5 on Railwail yet to state a run time. It depends on the input, the settings and the load at the provider.

Is GTE Large EN v1.5 better than OpenAI text-embedding-3-large?

That depends on the task. GTE Large EN v1.5 (Community) and OpenAI text-embedding-3-large (OpenAI) are both models in the Embeddings category. The comparison page shows their prices and specifications side by side.

Compare GTE Large EN v1.5 and OpenAI text-embedding-3-large

Can I use GTE Large EN v1.5 right now?

Currently unavailable. The page stays online; available alternatives from the same category are listed further down.

All models through one API

One API key for every model on Railwail. Usage is charged from prepaid credits, 1 credit = $0.01.

Get API key Browse all models