midm-k-3-0-pro
Mi:dm K 3.0 Pro is a mixture-of-experts reasoning model from KT with 120B total and 12B active parameters, using a hybrid architecture that mixes Mamba, MoE and attention layers.
Pricing: Input 48 credits / 1M tokens (≈ $0.24), Output 192 credits / 1M tokens (≈ $0.96).
Prices updated
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Mi:dm K 3.0 Pro API on ModelFold
Mi:dm K 3.0 Pro is a mixture-of-experts reasoning model from KT with 120B total and 12B active parameters, using a hybrid architecture that mixes Mamba, MoE and attention layers. Try Mi:dm K 3.0 Pro in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Mi:dm K 3.0 Pro API
Mi:dm K 3.0 Pro at a glance
Mi:dm K 3.0 Pro is a chat model from KT. It accepts text as input and returns text, with a context window of up to 262K tokens.
Use it without hosting anything
On ModelFold you call Mi:dm K 3.0 Pro with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Mi:dm K 3.0 Pro
Up to 262K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Reasoning mode
Mi:dm K 3.0 Pro can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Mi:dm K 3.0 Pro on ModelFold
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Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Mi:dm K 3.0 Pro responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
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Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "midm-k-3-0-pro" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Mi:dm K 3.0 Pro
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Multilingual products
Serve users in many languages with translation, localized support replies and cross-language search.
Frequently Asked Questions
What is Mi:dm K 3.0 Pro?⌄
Mi:dm K 3.0 Pro is a mixture-of-experts reasoning model from KT with 120B total and 12B active parameters, using a hybrid architecture that mixes Mamba, MoE and attention layers.
Which inputs does Mi:dm K 3.0 Pro support?⌄
Mi:dm K 3.0 Pro accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Mi:dm K 3.0 Pro?⌄
Up to 262K tokens, shared between your input and the model’s output.
Does Mi:dm K 3.0 Pro support function calling?⌄
Function calling is not listed for Mi:dm K 3.0 Pro; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Mi:dm K 3.0 Pro billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Mi:dm K 3.0 Pro through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "midm-k-3-0-pro", using your ModelFold API key as the Bearer token.
| Input | 48 credits 1M tokens≈ $0.24 |
| Output | 192 credits 1M tokens≈ $0.96 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"midm-k-3-0-pro","messages":[{"role":"user","content":"Hello"}]}'