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BAAI: bge-m3

baai/bge-m3

Model weights

The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.

Modalities

Price

$0.01/M tokens

Context

8K

Released

Nov 18, 2025

ProvidersPricingPerformanceUptimeAppsActivityFAQ

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

Quick Start

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

About BAAI: bge-m3

OpenRouter makes BAAI: bge-m3 available through a unified, OpenAI-compatible API using the model ID baai/bge-m3. Requests can be routed across 2 providers, including DeepInfra and Parasail, with automatic failover when an endpoint is unavailable.

BAAI: bge-m3 accepts text and returns embedding vectors. It has a 8,194-token context window.

On OpenRouter, BAAI: bge-m3 costs $0.01/M tokens. It was released on November 18, 2025.

More models from BAAI

  • bge-base-en-v1.5
  • bge-large-en-v1.5

Frequently asked questions

The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.

bge-m3 costs $0.01/M tokens.

bge-m3 accepts up to 8,194 tokens per input. Longer text has to be split into multiple inputs.

bge-m3 accepts text as input and returns embedding vectors.

bge-m3 is served by 2 providers on OpenRouter: DeepInfra and Parasail. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

bge-m3 was released on November 18, 2025.

$0.01--
100.00%
$0.01--
99.99%
Uptime (3d)

100.00%

Availability (3d)

99.99%

Availability over the last 3 days

Last 72 hours
Availability 99.99%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.99%
Without Routing
98.99%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

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