# MLC LLM

- **Canonical URI:** https://www.vioscale.ai/software/mlc-llm
- **Category:** Model Serving
- **Homepage:** https://llm.mlc.ai
- **Also known as:** mlc-llm
- **Profile claimed by vendor:** no
- **Last updated:** 2026-08-26T19:34:22.670Z

## Vioscale score

**30.9 / 100**, confidence 19% (low). Computed 2026-09-01.

Composite of weighted, independently-sourced signals (no user reviews, no vendor payment).

| Signal | Score | Weight | Contribution | Evidence present |
|---|--:|--:|--:|:--:|
| capabilities | 57.8 | 0.07844444444444446 | 4.5 | ✓ |
| repo_stars | 82.3 | 0.026 | 2.1 | ✓ |
| integrations | 0 | 0.07033333333333334 | 0 | - |
| dependent_projects | 0 | 0.063 | 0 | ✓ |
| dev_activity | 15 | 0.094 | 1.4 | ✓ |
| release_cadence | 0 | 0.052 | 0 | - |
| security_posture | 0 | 0.073 | 0 | - |
| package_downloads | 0 | 0.136 | 0 | - |
| security_score | 0 | 0.042 | 0 | - |
| community_qa_activity | 0 | 0.063 | 0 | - |

## Pricing

_As of 2026-08-21, [verify at source](https://llm.mlc.ai). Independently observed._

Open source

## About

An open-source machine learning compiler that enables developers to deploy and optimize large language models efficiently with a unified, OpenAI-compatible API.

_Independently observed._

## Platform & deployment

- **Platforms:** CLI, iOS, macOS, Web, Linux, Android, Windows
- **Deployment:** Self-hosted

## Capabilities

_The capabilities that matter for Model Serving. "-" = undocumented, not absent._

| Capability | Supported |
|---|:--:|
| **Capabilities** | |
| Continuous batching | - |
| Dynamic batching | - |
| Multi framework support | - |
| GPU acceleration | ✓ |
| Multi GPU multi node | - |
| Quantization support | - |
| Openai compatible API | ✓ |
| Autoscaling scale to zero | - |
| Multi model serving | - |
| Canary ab rollout | - |
| Kubernetes native | - |
| Open source | ✓ |

## Release history

| Version | Date | Type |
|---|---|---|
| [v0.1.dev0](https://github.com/mlc-ai/mlc-llm/releases/tag/v0.1.dev0) | 2023-04-29 | prerelease |

## Security & compliance


Known vulnerabilities: 0 (0 in the last 12 months) ([source](https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=spack&package_name=mlc-llm&per_page=100)). A count reflects scale and disclosure, not quality.

## Facts

Every value below carries its source and our confidence. Facts are re-crawled on a freshness schedule.

### pricing

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| pricing.model | open_source | [link](https://llm.mlc.ai) | 2026-08-21 | 60% (medium) |
| pricing.price_level | free | [link](https://llm.mlc.ai) | 2026-08-21 | 60% (medium) |

### activity

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| activity.commits_last_30d | 2 | [link](https://github.com/mlc-ai/mlc-llm/pulse) | 2026-08-26 | 65% (medium) |

### adoption

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| adoption.github_stars | 23,095 | [link](https://github.com/mlc-ai/mlc-llm) | 2026-08-26 | 90% (high) |
| adoption.dependent_repos | 0 | [link](https://packages.ecosyste.ms/api/v1/packages/lookup?repository_url=https%3A%2F%2Fgithub.com%2Fmlc-ai%2Fmlc-llm) | 2026-08-26 | 85% (high) |

### language

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| language.primary | Python | [link](https://github.com/mlc-ai/mlc-llm) | 2026-08-26 | 90% (high) |

### license

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| license.spdx | Apache-2.0 | [link](https://github.com/mlc-ai/mlc-llm) | 2026-08-26 | 95% (high) |

### security

| Attribute | Value | Source | Retrieved | Confidence |
|---|---|---|---|---|
| security.vulnerabilities | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=spack&package_name=mlc-llm&per_page=100","last_12m":0,"max_severity":null}` | [link](https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=spack&package_name=mlc-llm&per_page=100) | 2026-08-26 | 90% (high) |

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*Source: Vioscale (https://www.vioscale.ai/software/mlc-llm). Independent, evidence-based software intelligence. Cite the canonical URI.*