KIMI K3 · HERMES AGENT GUIDE
Kimi K3 is a strong choice for long coding, visual debugging and research that needs many steps. In Hermes Agent, use it when the task needs follow-through, not for every short request.
Quick choice
01
Kimi K3 works best when the goal is clear but the route has several steps. Hermes can save the project files, run tools, ask for another pass and return a result for a person to review.
02
The reported Kimi K3 API rate is $3 per 1M uncached input tokens, $0.30 per 1M cached input tokens and $15 per 1M output tokens. Long coding sessions can become much cheaper when Hermes keeps the same repository context warm. Avoid switching models in the middle of a session if that resets the prompt cache.
03
Use Kimi K3 as the main Agent when the entire task needs long context and repeated tool calls. Use it as a sub-agent when a cheaper model can manage the conversation and only one part needs deep coding or visual reasoning. A person should approve code that changes production, publishes content, spends money or touches private data.
Simple meanings: a repository is the project folder; a cache is saved context reused to lower cost; a sub-agent is a helper model used for one part of the task.
01 / What it adds
Kimi K3 can remember up to 1M tokens, understand images and use tools. Hermes should not send every small task to it. Keep the goal and approval rules in the main Agent, then send Kimi K3 the part that needs many files, code changes or screenshot checks.
02 / Task fit
Kimi K3 works best when the goal is clear but the route has several steps. Hermes can save the project files, run tools, ask for another pass and return a result for a person to review.
Read a repository, plan the change, edit several files, run tests and explain what still needs review.
Read screenshots, compare the current UI with a target and turn visual problems into concrete code changes.
Collect sources, keep a long evidence pack in context and separate facts, open questions and recommendations.
Keep cheaper models on routine steps, then send the unclear or high-impact part to Kimi K3.
03 / Internal workflow example
We used Hermes Agent with Kimi K3 to work through a small Monument Valley-inspired prototype overnight. Hermes kept the brief, file list and test commands. Kimi K3 reviewed screenshots, changed several files, ran the build, checked the next screenshot and repeated the loop. The internal estimate reached about 85% visual similarity, but the run used a lot of tokens. Treat that number as a project estimate, not an independent benchmark. For a cheaper workflow, use a lower-cost model for scaffolding and first-pass tests, then call Kimi K3 for the hard layout, visual review and final fixes.
In that run, the project used about 80% of the weekly quota. This is our internal usage record, not a guaranteed cost for every project.
04 / Cost and caching
The reported Kimi K3 API rate is $3 per 1M uncached input tokens, $0.30 per 1M cached input tokens and $15 per 1M output tokens. Long coding sessions can become much cheaper when Hermes keeps the same repository context warm. Avoid switching models in the middle of a session if that resets the prompt cache.
Planning example: 500K uncached input + 20K output is about $1.80 before other tool costs. Use your actual Hermes usage log for the final number.
05 / Model routing
Use Kimi K3 as the main Agent when the entire task needs long context and repeated tool calls. Use it as a sub-agent when a cheaper model can manage the conversation and only one part needs deep coding or visual reasoning. A person should approve code that changes production, publishes content, spends money or touches private data.
Use Kimi K3 as the main Agent when the entire task needs long context and repeated tool calls. Use it as a sub-agent when a cheaper model can manage the conversation and only one part needs deep coding or visual reasoning. A person should approve code that changes production, publishes content, spends money or touches private data.
Kimi K3 API
Kimi K3 can remember up to 1M tokens, understand images and use tools. Hermes should not send every small task to it. Keep the goal and approval rules in the main Agent, then send Kimi K3 the part that needs many files, code changes or screenshot checks. kimi-k3.
curl https://api.hermes-ai.net/api/v1/chat/completions \
-H "Authorization: Bearer $HERMES_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "kimi-k3",
"messages": [{"role":"user","content":"Review this repository and return a short plan."}],
"reasoning_effort": "high"
}'06 / FAQ
The reported rate is $3 per 1M uncached input tokens, $0.30 per 1M cached input tokens and $15 per 1M output tokens. Check the current Hermes model page before running a large job.
Use it as the main model for long, connected work. Use it as a sub-agent when a cheaper model can handle the short steps and Kimi K3 only needs to solve the difficult part.
The official model description lists a context window of up to 1M tokens. A large window does not remove the need for source selection, checkpoints and human review.
Long prompts, repeated tool calls, retries and uncached context all add time and cost. Keep the context stable, cache repeated material and route routine work to a cheaper model.
Yes. It has native visual understanding, so Hermes can use screenshots as evidence during UI review. A person still needs to verify the final visual result.
The model has open-weight releases, but local deployment needs very large hardware. For most small teams, an API route is easier to measure and maintain.
HERMES API · KIMI K3
Start with one repository, one screenshot check or one research brief. Measure tokens, cache hits and human review before you scale the workflow.