MoonshotAI: Kimi K2.7 Code vs Nous: Hermes 4 405B
A side-by-side comparison of MoonshotAI: Kimi K2.7 Code ($2.10 / 1M tokens) and Nous: Hermes 4 405B ($3.50 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| MoonshotAI: Kimi K2.7 Code | Nous: Hermes 4 405B | |
|---|---|---|
| Provider | Moonshot AI | Nous |
| Input | $2.10 / 1M tokens | $3.50 / 1M tokens |
| Output | $12.25 / 1M tokens | $10.50 / 1M tokens |
| Cache read | $0.56 / 1M tokens | $0.70 / 1M tokens |
| Context window | 262,144 | 131,072 |
| Max output | 235,929 | 117,964 |
| Input | text, image | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Jun 12, 2026 | Aug 26, 2025 |
Key differences
- MoonshotAI: Kimi K2.7 Code is 40% cheaper on input tokens.
- Nous: Hermes 4 405B is 14% cheaper on output tokens.
- MoonshotAI: Kimi K2.7 Code reads 2.0× more context (262,144 tokens).
- Only MoonshotAI: Kimi K2.7 Code supports tool calling.
- A request with 1,000 input and 500 output tokens costs $0.00823 with MoonshotAI: Kimi K2.7 Code and $0.00875 with Nous: Hermes 4 405B.
In depth
MoonshotAI: Kimi K2.7 Code is a text model from Moonshot AI, released on 12 June 2026. Nous: Hermes 4 405B is a text model from Nous, released on 26 August 2025. Both are served through api14 as text generation models, and both accept text input and return text output. The main structural difference between them is age and lineage: Kimi K2.7 Code comes from a provider that has focused its recent work on coding assistance, while Hermes 4 405B is a large general model from Nous.
The two models differ most clearly in context window and input handling. Kimi K2.7 Code supports a context length of 262,144 tokens and accepts both text and image input. Hermes 4 405B supports a context length of 131,072 tokens and accepts text input only. So Kimi K2.7 Code gives you roughly twice the working room and the option to include images in a request, while Hermes 4 405B is text only. On parameters, Kimi K2.7 Code exposes a wider set, including tools, tool_choice, parallel_tool_calls, logit_bias, min_p and seed. Hermes 4 405B supports a narrower set that covers the common sampling and formatting controls but does not list tools or tool_choice. Neither model is listed as uniquely better at structured outputs or reasoning; those fields are not meaningfully different between them.
For practical selection, Kimi K2.7 Code is the natural choice when the task involves code, long files or repositories that need to fit in one request, or when you want to pass a screenshot, diagram or other image alongside text. Its tool support also makes it the pick for agent style workflows where the model has to call functions or run multi step tool loops. Hermes 4 405B fits general text work where the input is plain text and stays within 131,072 tokens: drafting, summarisation, question answering and similar tasks. If your prompts are text only and comfortably inside the smaller window, Hermes 4 405B is a reasonable default.
Calling either model through api14 works the same way. Both are OpenAI compatible, so you point your client at the api14 base URL and send a chat completions request. The only thing you change between the two is the model id: use "moonshotai/kimi-k2.7-code" for Kimi K2.7 Code and "nousresearch/hermes-4-405b" for Hermes 4 405B. Your request shape, authentication and response parsing stay identical, so you can switch models per request or compare outputs without rewriting integration code. Just check that any parameters you send are in the model's supported list, since Hermes 4 405B does not accept tool related fields.
On price, Kimi K2.7 Code is the cheaper option for input tokens, while Hermes 4 405B is cheaper for output tokens. The live price table on this page shows the current numbers, so weigh your expected input to output ratio when choosing. If your workload is input heavy, such as long documents or large code contexts, Kimi K2.7 Code tends to cost less overall; if you generate long outputs from short prompts, Hermes 4 405B can be the better value.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "moonshotai/kimi-k2.7-code" to "nousresearch/hermes-4-405b" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "nousresearch/hermes-4-405b",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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