Model Explorer
Technical Specifications
Detailed technical parameters and capabilities
- Context Window
- —
- Max Output
- 4,096 tokens
- Training Cutoff
- April 2024
- Tokenizer
- cl100k_base
Quick Integration
Get started with a single API call
quickstart.py
import openai
client = openai.OpenAI(
base_url="https://api.example.com/v1",
api_key="sk-ms-...",
)
response = client.chat.completions.create(
model="bge-m3",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
Performance Benchmarks
How bge-m3 compares across industry benchmarks
MMLU
95%vs 86.4%
HumanEval
90%vs 67%
GSM8K
93%vs 92%
bge-m3
GPT-4o Reference
Pricing
Pay-as-you-go
Standard Pricing
No commitments, pay only for what you use
Input$0.0001 per 1M tokens
Output$0.00 per 1M tokens
Indicative pricing — final cost is confirmed at request time.