Sold by: JetBrains Americas
Deployed on AWS
Mellum Kotlin is JetBrains' large language model (LLM) optimized for code completion in Kotlin and Java languages.
Overview
Mellum Kotlin is JetBrains' large language model (LLM) optimized for code completion in Kotlin and Java languages.
Highlights
- LLaMA-like architecture with ~4B parameters.
- Context-aware code completion with fill-in-the-middle.
- Top quality-to-size ratio.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimensions summary
The software itself is free; you pay only for the AWS compute instances that run model inference. You choose from eight options, each tied to a specific instance type and billed per host hour. One ml.g5.2xlarge option runs in batch mode for processing grouped requests. The remaining options run in real-time mode for interactive responses, spanning instance types from ml.g5.2xlarge through the larger p-series instances like ml.p5e.48xlarge. Pricing scales with the instance you select, so larger, higher-capacity GPU instances cost more per hour. Pick the instance that matches your workload size and latency needs.
Top-of-mind questions for buyers
One HostHrs unit is one hour that a single model inference instance runs. You are charged per active hour on the instance type you select. Counting is based on running time, so partial usage accrues by the hour the instance stays active.
Both meter per host hour on the running instance. The ml.g5.2xlarge batch option processes grouped requests together, which suits scheduled or bulk jobs. Real-time options handle interactive requests as they arrive, suiting low-latency workflows. Your cost still depends on how many hours the instance runs.
Charges apply per hour the instance runs. A fully stopped instance does not accrue software inference charges. Underlying AWS resources such as attached storage may still bill separately, but the model inference charge meters running host time only.
www.jetbrains.com
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
First version available to enterprise customers.
Additional details
Inputs
- Summary
Model input should be application/json. See the input parameters and sample input data for more information.
- Input MIME type
- application/json
{"prefix": "import js", "suffix": "\n", "filepath": "main.py", "context": [], "max_length": 32, "stop_token": "\n\n", "use_control": "off"}
{"prefix": "import js", "suffix": "\n", "filepath": "main.py", "context": [], "max_length": 32, "stop_token": "\n\n", "use_control": "off"}
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
prefix | Code that appears before the cursor. | string | Yes |
suffix | Code that appears after the cursor. | string | Yes |
filepath | Relative path of the file being edited, including file name and extension (e.g. 'src/utils/helpers.ts'). | string | Yes |
context | Additional context items (such as neighbouring files, docs, etc.) | list | No |
max_length | Maximum number of BPE tokens that may be generated for the completion snippet. | integer | Yes |
stop_token | String at which generation should stop (exclusive). | string | No |
use_control | Selects the Cloud-Control mode. Use 'off' if unsure. | "on","off","silent" | Yes |
generate_indents | Whether the model should emit indentation characters. | boolean | No |
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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