169Pi / 169pi/alpie-core
Alpie Core - access through LLMTR
Alpie Core is 169Pi's 32-billion-parameter, 4-bit quantized reasoning model. Use it for maths, code and multi-step logic. It reasons before every answer and this cannot be turned off; the trace arrives in reasoning_content and its tokens are billed as output. It takes text only, with no tool calling or structured output. The context window is 65,000 tokens and a single response can reach 16,384. On very short prompts with no context the answer can be off-topic, so write your question with its context.
Technical specifications
| Canonical ID | 169pi/alpie-core |
|---|---|
| Provider | 169Pi |
| Context window | 65,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | $0.150000 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $0.400000 |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"169pi/alpie-core","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- Alpie Core API: first request with LLMTR - Alpie Core is called on LLMTR as 169pi/alpie-core through https://llmtr.com/v1/chat/completions. The context window is 65,000 tokens and input is text only. The price is $0.15 input and $0.40 output per 1M tokens; a 200-token prompt with 500 output tokens costs $0.00023.
- What is a 4-bit quantized model? Alpie Core memory and cost - A 4-bit quantized model stores each weight in 4 bits; against 16 bits the weight memory falls to a quarter, and accuracy has to be evaluated per task. Alpie Core is called on LLMTR as 169pi/alpie-core through https://llmtr.com/v1/chat/completions; 169Pi has opened the weights under Apache 2.0.
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