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Kimi K2.5

Moonshot AI's open-weight multimodal model for agentic and tool-using workflows.

Visit official site Open repository
Modified MIT License
Kimi K2.5 Modified MIT License platform.moonshot.ai verified 2026-04-19
About

Kimi K2.5 overview

Kimi K2.5 is Moonshot AI's powerful open-weight model line, positioned for multimodal and agentic workflows with API access and public model materials.

✦

Agentic model positioning

Kimi K2.5 is marketed around tool use and agentic tasks rather than only chat.

That makes it a serious candidate for OpenAgent-style workflows.
✦

Open-weight distribution

Moonshot publishes public repository and model access materials for evaluation.

Open weights let builders compare behavior outside a single hosted interface.
✦

Multimodal direction

The Kimi K2.5 line is positioned as a multimodal model rather than a text-only assistant.

Multimodal inputs are increasingly important for agents that read screens, documents, and visual context.
Use cases

When to use Kimi K2.5

Agent model comparison

Evaluate Kimi K2.5 against Qwen, GLM, and DeepSeek-style models on tool-using workflows.

Coding and repository tasks

Test whether it can reason across code, instructions, and tool calls in realistic engineering loops.

Multimodal assistant prototypes

Use it as a candidate when an assistant needs more than plain text input.

Compare

How it compares

Strong candidate for open-weight agent testing vs Qwen3.6 and GLM-5

Kimi K2.5 is useful when the comparison target is agentic behavior and multimodal capability, but its modified license terms should be reviewed carefully.

FAQ

Questions

What should I check before using Kimi K2.5?

Run Kimi K2.5 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.

Is Kimi K2.5 open source?

Kimi K2.5 is listed with Modified MIT based on the official source links in this profile. Re-check the repository, model card, or docs before production use.

Who should evaluate Kimi K2.5?

Kimi K2.5 is most worth evaluating for teams comparing open-weight models for tool-using agents.

Tags

Capabilities

tool callingworkflow orchestrationlocal inferencesource availableopen weightsdeveloper workflow
Decision brief

Should you use Kimi K2.5?

JSON
Best for
  • Teams comparing open-weight models for tool-using agents
  • Developers testing coding and reasoning workflows with Kimi-compatible APIs
  • Researchers watching how Chinese open model labs approach multimodal agents
Not for
  • Teams that require a pure OSI-style open-source license without extra model terms
  • Users who want a local-only consumer app with no API or model operations work
Trust and freshness
  • Verified 2026-04-19
  • License: Modified MIT
  • Repo: MoonshotAI/Kimi-K2.5
  • Open-source status needs review
Deployment

cloud

Permission surface

shell/files, external services

Decision signals

No extra signals recorded

Agent packet

Structured decision data for Kimi K2.5

This packet is the compact machine-readable view agents should use before following source links or taking action.

Full JSON Agent packet Markdown brief
Capabilities

tool calling, workflow orchestration, local inference

Constraints

source available, open weights

Deployment

cloud

Permission surface

shell/files, external services

Recommended workflows

Coding agent workflow, Local or private AI stack

Overview

What Kimi K2.5 does

What it is

Kimi K2.5 is an open model resource to evaluate by workload, serving path, context behavior, license terms, and how reliably it supports the agent or local AI tasks you actually plan to run.

Why it matters

Kimi K2.5 matters because it sits at the intersection of frontier-style agent behavior and open model distribution. For teams comparing model choices for coding, tool use, and multimodal tasks, it is one of the models worth evaluating closely.

How to evaluate it

Run Kimi K2.5 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.

Facts

Known metadata and operating surface

These fields are separated from editorial interpretation so agents can reason over facts and missing checks.

Resource type model
Category Models
Maturity active
Difficulty Unknown
License Modified MIT
Pricing free
Verified 2026-04-19
Source confidence high
Risk level elevated
Fit matrix

Where Kimi K2.5 fits in an agent stack

strong

Coding agent workflow

Kimi K2.5 has multiple signals for coding agent workflow, including matching tags, capabilities, category, or positioning.

  • Run a small repository change and inspect the diff, tests, and rollback path.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong

Local or private AI stack

Kimi K2.5 has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning.

  • Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial

Connector or protocol layer

Kimi K2.5 has at least one signal for connector or protocol layer, but should be checked against a real task before adoption.

  • Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial

Evaluation and observability

Kimi K2.5 has at least one signal for evaluation and observability, but should be checked against a real task before adoption.

  • Add one repeatable test case and confirm results can run again in review or CI.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial

Reusable skill workflow

Kimi K2.5 has at least one signal for reusable skill workflow, but should be checked against a real task before adoption.

  • Run one skill end to end and check whether it produces evidence or structured output.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak

Browser automation

Kimi K2.5 is not primarily positioned for browser automation in the current metadata.

  • Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
  • Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs

What an agent should inspect

Likely inputs

  • Repositories, files, issues, terminal output, and test results
  • Tool schemas, API requests, service resources, and auth scopes
  • Prompts, messages, documents, images, or model inputs
  • Official setup instructions and a small real workflow

Likely outputs

  • Diffs, commits, explanations, test results, or review notes
  • A decision on whether this resource fits the target workflow
Evidence

Sources, claims, and missing checks

Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.

GitHub github

Repository source for code, license, issues, releases, and implementation details.

 Homepage homepage

Official or project-controlled source for this resource profile.
verified

Kimi K2.5 is not currently marked as open source in OpenAgent metadata.

License metadata: Modified MIT
verified

Kimi K2.5 has a recorded GitHub repository: MoonshotAI/Kimi-K2.5.

Resource facts and GitHub source link.
inferred

Kimi K2.5 supports these recorded deployment modes: cloud.

OpenAgent decision signal metadata.
inferred

Kimi K2.5 is tagged with tool calling, workflow orchestration, local inference capabilities.

OpenAgent capability taxonomy.
Missing checks
  • Dedicated docs link is missing.
  • Repository freshness has not been recorded.
Next action

How to start evaluating Kimi K2.5

Inspect repository

Check license, recent activity, issues, examples, and security-sensitive code paths.

Open source

Open Homepage

Start from the official source before adopting third-party instructions.

Open source

Clone the model repository

Start with official model materials and license notes before using it in production.

git clone https://github.com/MoonshotAI/Kimi-K2.5.git
Compare

Alternatives and nearby resources

Use related resources to compare category fit, license, deployment model, and first-workflow behavior.

Rapid-MLX

Apple Silicon local AI engine with OpenAI-compatible API, tool calling, prompt cache, and MLX acceleration.

Models LiteRT-LM

Google's open-source inference framework for deploying large language models on edge devices.

Models FinGPT

Open-source financial large language model project for finance sentiment, analysis, and domain adaptation.

Models
FAQ

Common questions about Kimi K2.5

What should I check before using Kimi K2.5?

Run Kimi K2.5 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.

Is Kimi K2.5 open source?

Kimi K2.5 is listed with Modified MIT based on the official source links in this profile. Re-check the repository, model card, or docs before production use.

Who should evaluate Kimi K2.5?

Kimi K2.5 is most worth evaluating for teams comparing open-weight models for tool-using agents.