Create a model alias

POST

api

llm

models

aliases

Go (SDK)

package main

import(
	"context"
	mka1 "github.com/MeetKai/mka1-sdks/go"
	"github.com/MeetKai/mka1-sdks/go/optionalnullable"
	"github.com/MeetKai/mka1-sdks/go/models/components"
	"log"
)

func main() {
    ctx := context.Background()

    s := mka1.New(
        mka1.WithSecurity("<YOUR_BEARER_TOKEN_HERE>"),
    )

    res, err := s.Llm.Models.CreateAlias(ctx, components.CreateModelAliasRequest{
        Name: "best-math-model",
        SuiteID: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
        Metric: "accuracy",
        CandidateModelIds: []string{
            "meetkai:functionary-pt",
            "meetkai:functionary-es",
        },
        DefaultModelID: optionalnullable.From(mka1.Pointer("meetkai:functionary-pt")),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.ModelAlias != nil {
        // handle response
    }
}

using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using System.Collections.Generic;

var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");

CreateModelAliasRequest req = new CreateModelAliasRequest() {
    Name = "best-math-model",
    SuiteId = "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    Metric = "accuracy",
    CandidateModelIds = new List<string>() {
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    },
    DefaultModelId = "meetkai:functionary-pt",
};

var res = await sdk.Llm.Models.CreateAliasAsync(req);

// handle response

from meetkai_mka1 import SDK


with SDK(
    bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:

    res = sdk.llm.models.create_alias(name="best-math-model", suite_id="eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a", metric="accuracy", candidate_model_ids=[
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    ], default_model_id="meetkai:functionary-pt")

    # Handle response
    print(res)

import { SDK } from "@meetkai/mka1";

const sdk = new SDK({
  bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
});

async function run() {
  const result = await sdk.llm.models.createAlias({
    name: "best-math-model",
    suiteId: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    metric: "accuracy",
    candidateModelIds: [
      "meetkai:functionary-pt",
      "meetkai:functionary-es",
    ],
    defaultModelId: "meetkai:functionary-pt",
  });

  console.log(result);
}

run();

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/models/aliases \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "metric": "accuracy",
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "default_model_id": "meetkai:functionary-pt"
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'best-math-model',
    suite_id: 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    metric: 'accuracy',
    candidate_model_ids: ['meetkai:functionary-pt', 'meetkai:functionary-es'],
    default_model_id: 'meetkai:functionary-pt'
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/models/aliases', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://apigw.mka1.com/api/v1/llm/models/aliases",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => 'best-math-model',
    'suite_id' => 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    'metric' => 'accuracy',
    'candidate_model_ids' => [
        'meetkai:functionary-pt',
        'meetkai:functionary-es'
    ],
    'default_model_id' => 'meetkai:functionary-pt'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/models/aliases")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/models/aliases")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}"

response = http.request(request)
puts response.read_body

{
  "object": "model.alias",
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "suite_version": 3,
  "metric": "accuracy",
  "higher_is_better": true,
  "task_id": null,
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "api_format": "responses",
  "default_model_id": "meetkai:functionary-pt",
  "pinned_model_id": null,
  "current_model_id": "meetkai:functionary-es",
  "served_model_id": "meetkai:functionary-es",
  "served_because": "benchmark",
  "state": "ok",
  "resolvable": true,
  "standings": [
    {
      "model_id": "meetkai:functionary-pt",
      "score": 0.81,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    },
    {
      "model_id": "meetkai:functionary-es",
      "score": 0.86,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    }
  ],
  "evaluated_at": "2026-11-09T02:14:05.000Z",
  "created_by": "user-org-admin-1",
  "created_at": "2026-11-01T18:00:00.000Z",
  "updated_by": "user-org-admin-1",
  "updated_at": "2026-11-01T18:00:00.000Z"
}

Authorizations

Authorization

string

header

required

Send Authorization: Bearer , using an MKA1 API key for automation or an OAuth API access token for a signed-in application. Use a dynamic security callback to refresh OAuth access tokens. Browser session-only operations still require their declared cookie.

Body

application/json

name

string

required

The model name callers use. It is claimed in the organization's registry, so it must not already be active.

Required string length: 1 - 255

suite_id

string

required

An eval suite owned by this organization.

Required string length: 1 - 255

metric

string

required

A metric id the suite's active version declares. Its higher_is_better decides which score wins.

Required string length: 1 - 128

candidate_model_ids

string[]

required

Two to 16 active models of one API format. The alias only ever serves one of these. Order breaks ties: the earlier model wins an equal score.

Required array length: 2 - 16 elements

Required string length: 1 - 255

task_id

string | null

A task of the suite to rank on. Null ranks the metric averaged over every task, counting only runs that cover every task of the version.

Required string length: 1 - 255

default_model_id

string | null

A candidate to serve until a first winner exists. Null leaves the alias unresolvable until then.

Required string length: 1 - 255

Response

200 - application/json

object

any

required

name

string

required

suite_id

string

required

suite_version

integer | null

required

The suite version the last recompute ranked. Null before one could be read.

Required range: -9007199254740991 <= x <= 9007199254740991

metric

string

required

higher_is_better

boolean | null

required

task_id

string | null

required

candidate_model_ids

string[]

required

api_format

enum<string>

required

Available options:

responses,

completions,

embeddings,

images,

transcriptions,

tts,

rerank

default_model_id

string | null

required

pinned_model_id

string | null

required

current_model_id

string | null

required

The benchmark winner. Null until one exists.

served_model_id

string | null

required

What a request for the alias is served by: the pin, else the winner, else the default.

served_because

enum<string> | null

required

Available options:

pinned,

benchmark,

default

state

enum<string>

required

ok: serving a ranked winner. waiting_for_results: no complete result to rank yet, so the last winner or the default holds. metric_missing: the suite's active version no longer declares the metric or task. suite_missing: the suite was deleted. The last two hold the last winner until the alias is edited.

Available options:

ok,

waiting_for_results,

metric_missing,

suite_missing

resolvable

boolean

required

Whether a request for the alias resolves right now: it serves a model that is still active in the registry.

standings

object[]

required

Show child attributes

evaluated_at

string<date-time> | null

required

created_by

string

required

created_at

string<date-time>

required

updated_by

string

required

updated_at

string<date-time>

required

⌘I

Go (SDK)

package main

import(
	"context"
	mka1 "github.com/MeetKai/mka1-sdks/go"
	"github.com/MeetKai/mka1-sdks/go/optionalnullable"
	"github.com/MeetKai/mka1-sdks/go/models/components"
	"log"
)

func main() {
    ctx := context.Background()

    s := mka1.New(
        mka1.WithSecurity("<YOUR_BEARER_TOKEN_HERE>"),
    )

    res, err := s.Llm.Models.CreateAlias(ctx, components.CreateModelAliasRequest{
        Name: "best-math-model",
        SuiteID: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
        Metric: "accuracy",
        CandidateModelIds: []string{
            "meetkai:functionary-pt",
            "meetkai:functionary-es",
        },
        DefaultModelID: optionalnullable.From(mka1.Pointer("meetkai:functionary-pt")),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.ModelAlias != nil {
        // handle response
    }
}

using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using System.Collections.Generic;

var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");

CreateModelAliasRequest req = new CreateModelAliasRequest() {
    Name = "best-math-model",
    SuiteId = "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    Metric = "accuracy",
    CandidateModelIds = new List<string>() {
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    },
    DefaultModelId = "meetkai:functionary-pt",
};

var res = await sdk.Llm.Models.CreateAliasAsync(req);

// handle response

from meetkai_mka1 import SDK


with SDK(
    bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:

    res = sdk.llm.models.create_alias(name="best-math-model", suite_id="eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a", metric="accuracy", candidate_model_ids=[
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    ], default_model_id="meetkai:functionary-pt")

    # Handle response
    print(res)

import { SDK } from "@meetkai/mka1";

const sdk = new SDK({
  bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
});

async function run() {
  const result = await sdk.llm.models.createAlias({
    name: "best-math-model",
    suiteId: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    metric: "accuracy",
    candidateModelIds: [
      "meetkai:functionary-pt",
      "meetkai:functionary-es",
    ],
    defaultModelId: "meetkai:functionary-pt",
  });

  console.log(result);
}

run();

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/models/aliases \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "metric": "accuracy",
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "default_model_id": "meetkai:functionary-pt"
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'best-math-model',
    suite_id: 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    metric: 'accuracy',
    candidate_model_ids: ['meetkai:functionary-pt', 'meetkai:functionary-es'],
    default_model_id: 'meetkai:functionary-pt'
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/models/aliases', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://apigw.mka1.com/api/v1/llm/models/aliases",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => 'best-math-model',
    'suite_id' => 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    'metric' => 'accuracy',
    'candidate_model_ids' => [
        'meetkai:functionary-pt',
        'meetkai:functionary-es'
    ],
    'default_model_id' => 'meetkai:functionary-pt'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/models/aliases")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/models/aliases")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}"

response = http.request(request)
puts response.read_body

{
  "object": "model.alias",
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "suite_version": 3,
  "metric": "accuracy",
  "higher_is_better": true,
  "task_id": null,
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "api_format": "responses",
  "default_model_id": "meetkai:functionary-pt",
  "pinned_model_id": null,
  "current_model_id": "meetkai:functionary-es",
  "served_model_id": "meetkai:functionary-es",
  "served_because": "benchmark",
  "state": "ok",
  "resolvable": true,
  "standings": [
    {
      "model_id": "meetkai:functionary-pt",
      "score": 0.81,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    },
    {
      "model_id": "meetkai:functionary-es",
      "score": 0.86,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    }
  ],
  "evaluated_at": "2026-11-09T02:14:05.000Z",
  "created_by": "user-org-admin-1",
  "created_at": "2026-11-01T18:00:00.000Z",
  "updated_by": "user-org-admin-1",
  "updated_at": "2026-11-01T18:00:00.000Z"
}

Overview

Responses and conversations

Models and routing

Images and audio

Files and retrieval

Agents

Tools and sandbox

Evals and feedback

Compute

Repositories

Dataset generations

Organizations and access

Usage and budgets

Application utilities

Analytics

Legacy APIs

Additional APIs

Create a model alias

Authorizations

Body

Response