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MoonshotAI: Kimi K3 vs Reflection Beam 1.0

Try both on us. Starter credit covers your first requests, then one key routes Kimi K3 and Reflection Beam 1.0. Switch by changing the model name.

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

MoonshotAI: Kimi K3 has more Credits provider routes and the lower measured p50 time to first token. Reflection Beam 1.0 has the lower published input-plus-output rate. Their context windows are the same size.

$11.97425/1MMoonshotAI: Kimi K3 cheapest route

$1.31875/1MReflection Beam 1.0 cheapest route

980 msMoonshotAI: Kimi K3 fastest measured p50 TTFT via lyceum

2491 msReflection Beam 1.0 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.

MoonshotAI: Kimi K3Reflection Beam 1.0

Model idmoonshotai/kimi-k3reflection/beam

Publisher Kimi reflection

AI IQ IQ 127#21 IQ 113#61

Context1,048,576 tokens1,048,576 tokens

Credits provider routes281

Cheapest route$11.97425/1M$1.31875/1M

Cached input$0.195175/1M to $1.897945/1MNot published

Privacy posturehas Confidential route (E2EE + ZDR)has ZDR route

Fastest measured p50 TTFT980 ms via lyceum2491 ms via nebius

Highest measured throughput172 tok/s via sail-researchnot enough data

Recent route uptime range50.00% to 100.00%100.00%

Modes chat chat

MoonshotAI: Kimi K3 routes

Overview28 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Reflection Beam 1.0 routes

Overview1 Credits routes

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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="moonshotai/kimi-k3",
    messages=messages,
)

Questions

Which should I use, MoonshotAI: Kimi K3 or Reflection Beam 1.0?

Is MoonshotAI: Kimi K3 or Reflection Beam 1.0 cheaper?

The current cheapest TrustedRouter route is $11.97425/1M for MoonshotAI: Kimi K3 and $1.31875/1M for Reflection Beam 1.0. The comparison uses current catalog prices and updates as provider pricing changes.

Is MoonshotAI: Kimi K3 or Reflection Beam 1.0 faster?

Current measured p50 time to first token is 980 ms for MoonshotAI: Kimi K3 and 2491 ms for Reflection Beam 1.0. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MoonshotAI: Kimi K3 and Reflection Beam 1.0 with the same API?

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