Mi:dm K 2.5 Pro Preview
Intelligence, Performance & Price Analysis
This profile does not provide this metric.
This profile does not provide this metric.
This profile does not provide this metric.
Decision Overview
Ethen's intelligence-driven routing assessment for this model
Overall verdict
General purpose assistant
Route complex or high-value tasks here when the extra capability justifies the cost.
Best for
Weak or unsuitable
- See model-fit matrix below
Routing recommendation
Use the fit matrix to compare against cheaper routes when volume rises
Cost pressure
Competitive pricing — $0.00 / M input, $0.00 / M output. Cost pressure is low enough for sustained production use.
Model-fit matrix
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Cost-sensitive pipelines | Excellent | Output pricing at $0.00 is very competitive for high-volume workloads. | Excellent for budget-constrained pipelines; enable caching to reduce costs further. |
Cost pressure
LowPricing is competitive — input $0.00, output $0.00. Suitable for sustained production use.
Cheaper substitutes
No cheaper substitute is supported by the current price data.
Route away when
- Extreme scale where even low costs matter
Highlights
Key benchmark results at a glance.
Intelligence
Intelligence position
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
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.
Speed
Speed position
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Higher throughput supports faster interactive use.
Context, Cost & Pricing
Price/value position
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is competitive — input $0.00, output $0.00. Suitable for sustained production use.
Intelligence & Quality
Benchmark scores and quality indices measuring model capability.
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.
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.
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.
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.
Speed & Throughput
Output tokens per second and generation throughput.
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.
Context, Cost & Pricing
Context window size, cost per task, and token pricing.
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.
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.
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.
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.
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.
Specifications
Technical Specifications
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.
Mi:dm K 2.5 Pro Preview
- Model type
- Open weights
- Reasoning
- Yes
- Input modalities
- Mi:dm K 2.5 Pro Preview supports text input.
- Output modalities
- Mi:dm K 2.5 Pro Preview supports text output.
- Context window
- 130k tokens
- Open weights / source
- No, Mi:dm K 2.5 Pro Preview is proprietary. The model weights are not publicly available.
- Parameters
- Mi:dm K 2.5 Pro Preview is a proprietary model and Korea Telecom has not disclosed the model size or parameter count.
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.