Kimi K2.7 Code

Kimi K2.7 Code on Zumik: live pricing, context, and caching, routable by id or alias through one OpenAI-compatible endpoint.

$0.95
Input / 1M tokens
$4.00
Output / 1M tokens
$0.19
Cache read · −80%
262K
Context window

At a glance.

ProviderFireworks AI
Familykimi_k25
Released2026-06
LicenseOpen weights
Context window262K tokens
Max output262K tokens
Parameters1029B
Modalitiestext, image
Tool callingYes
Reasoning modeYes
Cachingautomatic
Batch discountNo batch tier

What reuse looks like here.

Not yet profiled

Pricing, context, and capabilities for Kimi K2.7 Code are live, but it is outside the flagship set Zumik benchmarks in depth, so measured reuse, capture, and warm TTFT are not shown yet. Run a workload estimate or route it by id to start collecting traces.

Reuse economics

What you actually pay once caching works.

At a typical 55% prefix reuse, a million input tokens on Kimi K2.7 Code effectively costs $0.53 instead of $0.95 - blending to roughly $1.40 with a 25% output share. There is no batch tier, so cost control here leans on caching and routing.

Estimate it for your workload
Best for
textimage

Route it directly by id, or let an alias pick it when it wins under policy.

Same OpenAI client, this model.

python
from openai import OpenAI

client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")

r = client.responses.create(
    model="kimi-k2p7-code",
    input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached)   # confirm reuse

Kimi K2.7 Code, answered.

How much does Kimi K2.7 Code cost?

Kimi K2.7 Code is $0.95 per million input tokens and $4.00 per million output tokens through Zumik. Cache reads are $0.19 per million, a 80% discount on input.

What is Kimi K2.7 Code's context window?

Kimi K2.7 Code supports a 262K-token context window with up to 262K output tokens.

Run Kimi K2.7 Code with reuse measured.

Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.