Input Price
$0.00Korea Telecom · Flagships Analysis
Mi:dm K 2.5 Pro Preview
Intelligence, Performance & Price Analysis
Canonical slug: midm-250-pro-rsnsft · Canonical model registry at build time
Output Price
$0.00Executive Assessment
Routing Verdict & Tradeoffs
General purpose assistant
Analysis of Korea Telecom's Mi:dm K 2.5 Pro Preview and comparison to other AI models across key metrics including quality, price, performance (tokens per second & time to first token), context window & more.
Route complex or high-value tasks here when the extra capability justifies the cost.
Task Fit Assessment
| Workload | Rating | Notes |
|---|---|---|
| Cost-sensitive pipelines | optimal | Output pricing at $0.00 is very competitive for high-volume workloads. |
Cost Pressure Analysis
Low
Pricing is competitive — input $0.00, output $0.00. Suitable for sustained production use.
Technical Specifications
Architecture and Limits
| Specification | Value | Validation Authority |
|---|---|---|
| Model type | Proprietary | inferred |
| Reasoning | Yes | faq |
| Input modalities | Mi:dm K 2.5 Pro Preview supports text input. | faq |
| Output modalities | Mi:dm K 2.5 Pro Preview supports text output. | faq |
| Context window | 130k tokens | faq |
| Open weights / source | No, Mi:dm K 2.5 Pro Preview is proprietary. The model weights are not publicly available. | faq |
| Parameters | Mi:dm K 2.5 Pro Preview is a proprietary model and Korea Telecom has not disclosed the model size or parameter count. | faq |
Evidence charts
Profile visualizations
Charts are the same canonical evidence cards previously published for this slug, contained inside the D18D page grammar.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Methodology
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Mi:dm K 2.5 Pro Preview.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Frequently Asked Questions
Model FAQs & Technical Disclosures
Mi:dm K 2.5 Pro Preview was released on December 11, 2025.
Mi:dm K 2.5 Pro Preview was created by Korea Telecom.
Yes, Mi:dm K 2.5 Pro Preview is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Mi:dm K 2.5 Pro Preview supports text input.
Mi:dm K 2.5 Pro Preview supports text output.
No, Mi:dm K 2.5 Pro Preview does not support image input. It can only process text.
No, Mi:dm K 2.5 Pro Preview is not multimodal. It only supports text input.
Mi:dm K 2.5 Pro Preview has a context window of 130k tokens. This determines how much text and conversation history the model can process in a single request.
No, Mi:dm K 2.5 Pro Preview is proprietary. The model weights are not publicly available.
Mi:dm K 2.5 Pro Preview is a proprietary model and Korea Telecom has not disclosed the model size or parameter count.
Check the providers page for current API availability.
Visit the providers page to see availability.