GreenPT / greenpt/kimi-k3-eu
Kimi K3 - access through LLMTR
Kimi K3 has a 1,000,000-token context window, the widest and the most expensive row on this provider. It genuinely processes image input: in measurement it described a product photo correctly and its input token count rose by the image's own tokens. Tool/function calling was verified over a full two-turn loop — the model called the tool, consumed the tool result and produced a final answer. Repeated prompt prefixes are served from a cache and those input tokens bill at a quarter of the normal input rate. The model reasons by default: it spent hidden reasoning tokens even on a one-word question, and those tokens bill as output. Output costs five times input here, so price short requests from the output rate rather than the input one.
Same model, other providers: TensorX (EU) · Moonshot AI (Kimi) · Engy
Technical specifications
| Canonical ID | greenpt/kimi-k3-eu |
|---|---|
| Provider | GreenPT |
| Context window | 1,000,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text, image |
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 | $4.064029 |
| CHAT_COMPLETIONS | CACHE_READ | PER_1M_TOKENS | $1.016007 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $20.320146 |
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":"greenpt/kimi-k3-eu","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- The EU AI Act and LLM APIs: A Practical Guide for Developers - Reads the EU AI Act from the position of a developer consuming an LLM API: role, risk class and the record-keeping habits that follow.
- EU-Hosted LLM Models: Reading a 57-Row Catalog - Separates the EU category's 57 rows into chat, embedding, reranking and decisions, and gives a selection framework based on measured capabilities.
- How to Use GreenPT Models Through LLMTR - Covers using GreenPT rows through LLMTR, including the hidden system instruction and default reasoning that drive cost.
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