Sold by: JetBrains Americas
Deployed on AWS
Mellum Python is JetBrains' large language model (LLM) optimized for code completion in python.
Overview
Mellum Python is JetBrains' large language model (LLM) optimized for code completion in python.
Highlights
- LLaMA-like architecture with ~4B parameters.
- Context-aware code completion with fill-in-the-middle.
- Top quality-to-size ratio.
Details
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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 time used to run model inference. Charges apply per host hour on the instance type you select. One instance type offers both batch and real-time inference; the rest run in real-time mode only. Instance types range from single-GPU options to multi-GPU configurations, so pricing scales with the hardware you choose. Larger or newer GPU instances cost more per hour. You pick the instance that matches your latency, throughput, and workload needs, and billing follows that choice.
Top-of-mind questions for buyers
One HostHrs unit is one hour that a single inference instance runs. Billing meters the wall-clock hours the chosen instance type stays active. Each running instance accrues its own hourly charge. If you run several instances at once, each one counts separately toward your total hours.
Both modes bill per host hour on the ml.g5.2xlarge instance. Real-time mode keeps the endpoint running to serve immediate requests with low latency. Batch mode processes grouped inputs on demand. You choose the mode that fits your workload, and billing follows the hours the instance runs.
Charges apply per host hour while the instance runs. A fully stopped instance does not accrue inference host-hour charges. Underlying AWS resources, such as attached storage, may still incur separate AWS fees. The software itself is free; you pay only for active compute time on the instance you select.
www.jetbrains.com
Helpful?
Vendor refund policy
This product is free.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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.
Similar products
Mellum Python is JetBrains' large language model (LLM) optimized for code completion in python.
Mellum All is JetBrains' large language model (LLM) optimized for code completion in all languages.
JetBrains IDE Services is a developer experience suite that accelerates software development while making developer tools easy to manage at scale.
Mellum Kotlin is JetBrains' large language model (LLM) optimized for code completion in Kotlin and Java languages.
The ultimate CI/CD solution built to scale with your DevOps needs.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.