Kimi K2.7 Code: Same Trillion Parameters, 30% Fewer Tokens
Moonshot AI shipped Kimi K2.7 Code — a model that beats its own predecessor on coding while spending roughly 30% fewer tokens to get the same results. The efficiency story is the real headline.
TL;DR
- ⚡ ~30% fewer tokensthan K2.6 for the same or better coding results — that's a direct cost cut on every task.
- 🧠 Still a 1-trillion-parameter MoE model — strong, but big enough that self-hosting stays hard.
- 📜 Same open license as K2.6 — weights are out.
- 💸 Token efficiency compounds: fewer tokens × open-weight pricing on the MegaBrain gateway = cheaper agent runs.
What shipped
Kimi K2.7 Code is simultaneously better at coding than K2.6 and uses about 30% fewer tokens to reach those results. The license is unchanged, and the model is still a trillion-parameter network — which keeps independent self-hosting expensive. The open-source frontier keeps closing the gap.
| Kimi K2.6 | Kimi K2.7 Code | |
|---|---|---|
| Coding quality | Baseline | Better |
| Tokens to reach result | Baseline | ~30% fewer |
| Total params | 1T (MoE) | 1T (MoE) |
| License | Open weight | Same open weight |
| Self-host difficulty | High | High (1T params) |
Why fewer tokens matters
For an agent that runs all day, token count isthe bill. A model that produces the same answer in 30% fewer tokens isn't just faster — it's 30% cheaper per task and fits more work inside the same context budget. For long-running coding agents (the kind you run 24/7 on BrainClaw), that efficiency is the difference between a hobby loop and an affordable one.
Run it on MegaBrain
You don't need a GPU cluster to use a trillion-parameter model. Route it through the MegaBrain gateway with the same OpenAI-compatible API you already use:
import openai
client = openai.OpenAI(
base_url="https://getmegabrain.com/api/gateway/v1",
api_key="mb-your-key-here",
)
response = client.chat.completions.create(
model="moonshotai/kimi-k2.7-code",
messages=[{"role": "user", "content": "Refactor this module to async and add tests"}],
)Browse live pricing and the exact model ID on the models page. Switching models is a one-line change.
Source & further reading
Release spotted via @ai_newz. For the head-to-head against the other open-weight giant, see Kimi K2.7 Code vs GLM-5.2 →
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