KT: Mi:dm K 3.0 Pro pricing
Mi:dm K 3.0 Pro is a Mixture-of-Experts reasoning model from KT, with 120B total and 12B active parameters. It uses a hybrid architecture that mixes Mamba, MoE and attention layers. KT: Mi:dm K 3.0 Pro from OpenRouter costs $0.200 per 1M input tokens and $0.800 per 1M output tokens. Cached input is $0.040 per 1M. Context window 261,795 tokens.
API id kt/midm-k-3.0-pro · OpenRouter · source · updated 2026-11-11 · general-purpose
$0.200
Input / 1M tokens
$0.800
Output / 1M tokens
$0.040
Cached input / 1M
262K
Context window
KT: Mi:dm K 3.0 Pro specifications
- Provider
- OpenRouter
- API id
kt/midm-k-3.0-pro- Model type
- general-purpose
- Context window
- 262K tokens
- Max output
- 236K tokens
- Currency
- USD
- Price source
- Provider API
- Last checked
- 2026-11-11
Tags
- flagship
What KT: Mi:dm K 3.0 Pro costs in practice
| Workload | Input tokens | Output tokens | Estimated cost |
|---|---|---|---|
| Short chat turn | 1,000 | 500 | $0.0006 |
| Document summary | 50,000 | 2,000 | $0.01 |
| 1M tokens in, 200K out | 1,000,000 | 200,000 | $0.36 |
Estimates use the standard tier and ignore caching discounts, so real bills with repeated prompt prefixes are typically lower.
Common questions
- How much does KT: Mi:dm K 3.0 Pro cost per 1M tokens?
- KT: Mi:dm K 3.0 Pro costs $0.200 per 1M input tokens and $0.800 per 1M output tokens on the standard tier. Cached input is $0.040 per 1M.
- What is KT: Mi:dm K 3.0 Pro's context window?
- KT: Mi:dm K 3.0 Pro accepts up to 261,795 tokens in a single request, and can return up to 235,615 output tokens.
- Is there a cheaper OpenRouter model than KT: Mi:dm K 3.0 Pro?
- Yes. Free Models Router is free per 1M input tokens versus $0.200 for KT: Mi:dm K 3.0 Pro, with a 200,000 token context window.
- Where does this KT: Mi:dm K 3.0 Pro price come from?
- From the OpenRouter catalogue, because OpenRouter does not publish machine-readable pricing. OpenRouter is a reseller, so its rate can differ from OpenRouter's own — verify before committing spend.
Head-to-head comparisons
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