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OpenAI compatible API · Attested · Public status

Google: Gemini 3.8 Flash vs MoonshotAI: Kimi K3

Google: Gemini 3.8 Flash vs MoonshotAI: Kimi K3: compare current API pricing, context, provider routes, privacy, p50 latency, and OpenAI-compatible access.

Verify gateway
Onebase URL to migrate
100sof models and routes
0prompt or output logs. Always.
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

Monthly evidence

Google: Gemini 3.8 Flash has the lower published input-plus-output rate. MoonshotAI: Kimi K3 has more Credits provider routes and the lower measured p50 time to first token. Their context windows are the same size.

$4.7475/1MGoogle: Gemini 3.8 Flash cheapest route
$12.3435/1MMoonshotAI: Kimi K3 cheapest route
1840 msGoogle: Gemini 3.8 Flash fastest measured p50 TTFT via google-vertex
1172 msMoonshotAI: Kimi K3 fastest measured p50 TTFT via nebius

The price comparison adds each route's rate for one million input tokens and one million output tokens; your cost depends on your input/output mix. Prices and live route measurements can change. Use the monthly reports when you need a stable evidence window, then run a small task-specific eval before choosing a production default.

Google: Gemini 3.8 FlashMoonshotAI: Kimi K3
Model idgoogle/gemini-3.8-flashmoonshotai/kimi-k3
Context1,048,576 tokens1,048,576 tokens
Credits provider routes327
Cheapest route$4.7475/1M$12.3435/1M
Cached input$0.079125/1M$0.205725/1M to $1.74075/1M
Privacy posturehas ZDR routehas Confidential route (E2EE + ZDR)
Fastest measured p50 TTFT1840 ms via google-vertex1172 ms via nebius
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%0.00% to 100.00%
Modes chat chat

Google: Gemini 3.8 Flash routes

MoonshotAI: Kimi K3 routes

Related comparisons

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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="google/gemini-3.8-flash",
    messages=messages,
)

Questions

Which should I use, Google: Gemini 3.8 Flash or MoonshotAI: Kimi K3?

Google: Gemini 3.8 Flash has the lower published input-plus-output rate. MoonshotAI: Kimi K3 has more Credits provider routes and the lower measured p50 time to first token. Their context windows are the same size.

Is Google: Gemini 3.8 Flash or MoonshotAI: Kimi K3 cheaper?

The current cheapest TrustedRouter route is $4.7475/1M for Google: Gemini 3.8 Flash and $12.3435/1M for MoonshotAI: Kimi K3. The comparison uses current catalog prices and updates as provider pricing changes.

Is Google: Gemini 3.8 Flash or MoonshotAI: Kimi K3 faster?

Current measured p50 time to first token is 1840 ms for Google: Gemini 3.8 Flash and 1172 ms for MoonshotAI: Kimi K3. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Google: Gemini 3.8 Flash and MoonshotAI: Kimi K3 with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between google/gemini-3.8-flash and moonshotai/kimi-k3. This makes side-by-side evals possible without maintaining two provider integrations.

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