Analysis Summary
MoonshotAI's Kimi K2.5 is a capable multimodal model with a 262K context window, strong coding results, tool use, function calling, and a particularly strong measured tool-interaction result. Vision support broadens its usefulness to screenshots, design references, dashboards, and document workflows. Its general reasoning profile is below the latest flagship tier, but its practical engineering capability is much stronger than that gap suggests.
For Design for Online, Kimi K2.5 fits coding assistants, website maintenance, structured research, visual QA, and agents that need to call tools across several steps. The long context is useful for repositories, campaign documentation, and large briefs. Low listed input and output prices support regular production use. Use a stronger reasoning model for high-stakes strategy, while routing technical and multimodal work to Kimi where its cost and tool performance are advantageous.
Assessed September 7, 2026
Editorial notes
Kimi K2.5 combines strong coding, reliable tool use, vision, and a 262K context window at low listed prices. Its general reasoning is below flagship level, but it is a powerful choice for coding agents and multimodal production workflows.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Kimi K2.5 combines strong coding, reliable tool use, vision, and a 262K context window at low listed prices. Its general reasoning is below flagship level, but it is a powerful choice for coding agents and multimodal production workflows.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
27.6 Intelligence Index·46.8 Coding Index·21.7 Agentic Index
How MoonshotAI: Kimi K2.5 compares
MoonshotAI: Kimi K2.5 ranks #102 of 435 AI models we track for overall intelligence, #79 of 208 for coding, #79 of 190 for agentic tasks. Its 262K-token context window is larger than 71% of the models we list. At $0.45 per million input tokens it is cheaper than 40% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.45 | $0.000450 |
| Output | $2.25 | $0.002250 |
What would MoonshotAI: Kimi K2.5 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 756 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save MoonshotAI: Kimi K2.5 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout MoonshotAI: Kimi K2.5
Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed..
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Frequently asked questions about MoonshotAI: Kimi K2.5
How much does MoonshotAI: Kimi K2.5 cost?
MoonshotAI: Kimi K2.5 costs $0.45 per million input tokens and $2.25 per million output tokens.
What is the context window of MoonshotAI: Kimi K2.5?
MoonshotAI: Kimi K2.5 has a context window of 262,144 tokens (262K).
Is MoonshotAI: Kimi K2.5 good for coding?
On our coding benchmark index, MoonshotAI: Kimi K2.5 ranks #79 of 208 models, placing it in the broader range of the field for code generation and debugging.
What can MoonshotAI: Kimi K2.5 do?
MoonshotAI: Kimi K2.5 supports image/vision input, tool use, and function calling.
Who created MoonshotAI: Kimi K2.5?
MoonshotAI: Kimi K2.5 is developed by MoonshotAI and was released on January 27, 2026.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: September 7, 2026 8:38 pm