Measured on Composite
This model has not carried enough traffic on Composite yet to publish a success rate, a latency figure or a traffic rank. The numbers appear here once it has.
AI model
kt/midm-k-3.0-pro
KT: Mi:dm K 3.0 Pro is a 261,795-token model served on Composite at $0.250 per million tokens in and $1.00 per million tokens out.
Try in Playground| Model ID | kt/midm-k-3.0-pro |
|---|---|
| Provider | cv11 |
| Context window | 261,795 tokens |
| Accepts | text |
| Returns | text |
| Input price | $0.250 per million tokens |
| Output price | $1.00 per million tokens |
| Prompt caching | Supported — cached input is billed at the provider's cache rate, on credits and plans alike |
| Moderated | No |
| Cost on a monthly plan | About 2.4 plan credits per typical call (8k in, 1k out) |
| Routing endpoints | 2 (base plus 1 routing variant) |
This model has not carried enough traffic on Composite yet to publish a success rate, a latency figure or a traffic rank. The numbers appear here once it has.
The same model behind 1 alternative endpoint. Call the id directly to pin a route; the base id above picks for you.
| Route | Model ID | Provider | Price |
|---|---|---|---|
| cheapThink | kt/midm-k-3.0-pro:cheapThink |
cv11 | $0.250 per million tokens input · $1.00 per million tokens output |
$0.250 per million tokens input · $1.00 per million tokens output
Credits pay the provider’s price plus 25%; cache hits cost less.
On a monthly plan, a typical call (8k tokens in, 1k out) uses about 2.4 plan credits, at the provider's own price.
cv11
This model is available on Composite alongside dozens of others from other labs, so it is easy to compare against similar options.
With a 261,795-token context window, it can hold a long-running roleplay or a full lorebook in memory without losing earlier plot details, so it suits multi-session campaigns and character cards with heavy backstory.
It is priced low enough for high-volume daily roleplay without the per-message cost adding up quickly.
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.
Supplied by cv11, not written by Composite.
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