OpenAI compatible API. Attested gateway. Public status.

DeepSeek: DeepSeek V3.2 vs MoonshotAI: Kimi K2.7 Code

Compare DeepSeek: DeepSeek V3.2 and MoonshotAI: Kimi K2.7 Code by providers, context, price, and TrustedRouter route support.

Verify gateway

1 URLbase_url migration

100smodels and routes

0prompt logs by default

Compare routesProviders, price, context, and policy posture in one view.

Use auto when uptime mattersKeep a primary model and let fallback handle provider failures.

Same API shapeUse the OpenAI client and set the model you want.

Practical read

DeepSeek: DeepSeek V3.2 has the lower cheapest prompt+completion route on TrustedRouter. DeepSeek: DeepSeek V3.2 has more provider fallback routes, while MoonshotAI: Kimi K2.7 Code has the larger context window. Current TrustedRouter probes show DeepSeek: DeepSeek V3.2 with the lower p50 TTFT.

$0.7359/1MDeepSeek: DeepSeek V3.2 cheapest route

$5.445/1MMoonshotAI: Kimi K2.7 Code cheapest route

1773 msDeepSeek: DeepSeek V3.2 measured p50 TTFT

1954 msMoonshotAI: Kimi K2.7 Code measured p50 TTFT

DeepSeek: DeepSeek V3.2MoonshotAI: Kimi K2.7 Code

Model iddeepseek/deepseek-v3.2moonshotai/kimi-k2.7-code

PublisherDeepSeekKimi

Context163,840 tokens262,144 tokens

Provider routes74

Cheapest route$0.7359/1M$5.445/1M

Privacy posturehas provider E2EE routeprovider posture varies

Modes chat chat

DeepSeek: DeepSeek V3.2 routes

Overview7 endpoints
PricingPrompt and completion rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

MoonshotAI: Kimi K2.7 Code routes

Overview4 endpoints
PricingPrompt and completion rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Production choice

Pick a default model. Keep fallback enabled.

TrustedRouter is useful when you know the model you want, but still need provider rollover, budget limits, usage records, and a prompt path you can verify.

OpenAI clientPython

client = OpenAI(
    base_url="https://api.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v3.2",
    messages=messages,
)