Multimodal Visual Analysis
Kimi handles visual content with high precision, making it superior for tasks involving image analysis and multimodal data processing.
Kimi K2.5
The kimi k2.5 api delivers high-speed token generation and multimodal support. Grounded in Moonshot AI technology, kimi provides a cost-effective solution for web design, scripts, and creative roleplay with rock-solid infrastructure.
API Usage Examples
curl --request POST "https://gptproto.com/v1/chat/completions" \
--header "Authorization: Bearer $GPTPROTO_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "kimi-k2.5",
"messages": [
{
"role": "user",
"content": "Hello"
}
]
}'Kimi K2.5 pricing
Chat, coding agents & document work. Priced per 1M tokens — input, cached input and output are billed separately. GPTProto is 15% below official rates.
| Scenario | MoonshotAI list | OpenRouter | GPTProto | You save / mo |
|---|---|---|---|---|
| Personal10M tokens / mo (4.8M cached) | $8.40 | $8.86 | $7.14 | −$1.26≈ $15.12 / yr |
| Team100M tokens / mo (48M cached) | $84.00 | $88.62 | $71.40 | −$12.60≈ $151.20 / yr |
| Business500M tokens / mo (240M cached) | $420.00 | $443.10 | $357.00 | −$63.00≈ $756.00 / yr |
Save $0.00 / month
Annual savings ≈ $0.00 · pay as you go
Related Models
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Kimi K2.5Current
MoonshotAI · 262K context · $0.51/M input · $2.55/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Bytedance · 262K context · $0.0971/M input · $0.9714/M output
Model
Price: GPTProto
vs Official
vs OpenRouter
Context
Stability
Kimi K2.5Current
MoonshotAI
$0.51 / $2.55per 1M tokens
-15%
-19%
262K
Key Features of Kimi K2.5
Standout technical capabilities that make the kimi k2.5 api a leader in its class.
Rock-Solid Infrastructure
The kimi api cranks out tokens at lightning speed with minimal network drops, ensuring reliable performance for production use.
Attention Residuals Tech
Moonshot AI's AttnRes improves performance by selectively retaining important information across layers for better long-context memory.
Extreme Cost Efficiency
Get near-Opus performance at 1/15th the price. Kimi is the most cost-effective choice for scaling AI features without high overhead.
Kimi K2.5 API FAQ & Performance Guide
Common questions about implementing the kimi k2.5 api for your coding and creative projects.
How does the kimi k2.5 api handle heavy workloads?
Kimi is built on rock-solid infrastructure that produces tokens at lightning speed. Users report consistent performance with very few network drops or timeouts compared to competitors. It is specifically optimized for tasks that require quick turnaround, such as generating basic boilerplates or handling low-thinking grunt work, making it a reliable choice for high-volume production environments where latency is a primary concern.
Is the kimi k2.5 api good for complex coding?
Kimi is exceptional for web design, front-end tasks, and quick scripting. It works extremely well when integrated with tools like OpenCode. However, for deeply complex logic or heavy-lifting architectural coding, some developers prefer using kimi as a first pass before refining with a model like Claude Opus. Kimi handles build steps effectively but may occasionally be overly confident in its generated logic during highly complex tasks.
Does kimi support multimodal visual inputs?
Yes, the kimi k2.5 api is multimodal and performs significantly better with visual content than several other models in its class. This makes kimi a strong choice for applications that require analyzing images or processing data that combines text and visual elements. This multimodal capability allows kimi to follow visual prompts meticulously, making it versatile for both creative and technical visual workflows.
How does kimi compare to Claude Opus in cost?
Kimi is significantly more affordable, working nearly as well as high-end models at under 1/15th of the cost. For many use cases, users find no meaningful difference in output quality between kimi and more expensive alternatives like Opus, making the kimi k2.5 api an ideal solution for developers looking to scale their applications without the prohibitive costs associated with larger, proprietary models.
What is the prompt retention policy for Moonshot AI?
Moonshot AI generally retains user prompts to improve their products and fine-tune their models. While this helps kimi get better over time, it is an important consideration for business use cases requiring strict data privacy. Developers should review the current terms if they are working with highly sensitive data, though many find the performance gains from Moonshot's Attention Residuals technology to be worth the trade-off.
Why choose kimi over GLM-5 or MiniMax?
While GLM-5 offers high code quality, it can be painfully slow. MiniMax is fast but often viewed as less intelligent. Kimi sits in the sweet spot, offering better build steps and long-context handling than MiniMax, while maintaining much higher speeds than GLM-5. Kimi is particularly favored for roleplay and expressive prose, as it follows detailed prompts with a level of creativity and precision that its direct competitors often miss.
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