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deepseek-ai/DeepSeek-V3.1 vs MoonshotAI: Kimi K3

Try both on us. Starter credit covers your first requests, then one key routes deepseek-ai/DeepSeek-V3.1 and Kimi K3. 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

deepseek-ai/DeepSeek-V3.1 has the lower published input-plus-output rate. MoonshotAI: Kimi K3 has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

$1.266/1Mdeepseek-ai/DeepSeek-V3.1 cheapest route
$11.97425/1MMoonshotAI: Kimi K3 cheapest route
not enough datadeepseek-ai/DeepSeek-V3.1 fastest measured p50 TTFT
not enough dataMoonshotAI: Kimi K3 fastest measured p50 TTFT

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.

deepseek-ai/DeepSeek-V3.1MoonshotAI: Kimi K3
Model iddeepseek/deepseek-v3.1moonshotai/kimi-k3
Context163,840 tokens1,048,576 tokens
Credits provider routes428
Cheapest route$1.266/1M$11.97425/1M
Cached input$0.13715/1M to $0.241595/1M$0.195175/1M to $1.897945/1M
Privacy postureprovider posture varieshas Confidential route (E2EE + ZDR)
Fastest measured p50 TTFTnot enough datanot enough data
Highest measured throughputnot enough datanot enough data
Recent route uptime rangenot enough datanot enough data
Modes chat chat

deepseek-ai/DeepSeek-V3.1 routes

MoonshotAI: Kimi K3 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-azure.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v3.1",
    messages=messages,
)

Questions

Which should I use, deepseek-ai/DeepSeek-V3.1 or MoonshotAI: Kimi K3?

deepseek-ai/DeepSeek-V3.1 has the lower published input-plus-output rate. MoonshotAI: Kimi K3 has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

Is deepseek-ai/DeepSeek-V3.1 or MoonshotAI: Kimi K3 cheaper?

The current cheapest TrustedRouter route is $1.266/1M for deepseek-ai/DeepSeek-V3.1 and $11.97425/1M for MoonshotAI: Kimi K3. The comparison uses current catalog prices and updates as provider pricing changes.

Is deepseek-ai/DeepSeek-V3.1 or MoonshotAI: Kimi K3 faster?

Current measured p50 time to first token is not enough data for deepseek-ai/DeepSeek-V3.1 and not enough data for MoonshotAI: Kimi K3. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test deepseek-ai/DeepSeek-V3.1 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 deepseek/deepseek-v3.1 and moonshotai/kimi-k3. This makes side-by-side evals possible without maintaining two provider integrations.

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