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MoonshotAI: Kimi K2.5 vs Qwen3.8 Max

Try both on us. Starter credit covers your first requests, then one key routes Kimi K2.5 and Qwen3.8 Max. 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 K2.5 has the lower published input-plus-output rate and more Credits provider routes. Qwen3.8 Max has the larger context window. There is not enough recent probe data to compare speed.

$2.79575/1MMoonshotAI: Kimi K2.5 cheapest route

$6.964055/1MQwen3.8 Max cheapest route

not enough dataMoonshotAI: Kimi K2.5 fastest measured p50 TTFT

not enough dataQwen3.8 Max 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.

MoonshotAI: Kimi K2.5Qwen3.8 Max

Model idmoonshotai/kimi-k2.5qwen/qwen3.8-max

Publisher Kimi Alibaba Cloud Model Studio

AI IQ IQ 110#77 IQ 123#33

Context262,144 tokens1,000,000 tokens

Credits provider routes94

Cheapest route$2.79575/1M$6.964055/1M

Cached input$0.07385/1M to $0.422/1M$0.21733/1M to $0.26375/1M

Privacy posturehas ZDR routeprovider posture varies

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

MoonshotAI: Kimi K2.5 routes

Overview9 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Qwen3.8 Max routes

Overview4 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

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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="moonshotai/kimi-k2.5",
    messages=messages,
)

Questions

Which should I use, MoonshotAI: Kimi K2.5 or Qwen3.8 Max?

Is MoonshotAI: Kimi K2.5 or Qwen3.8 Max cheaper?

The current cheapest TrustedRouter route is $2.79575/1M for MoonshotAI: Kimi K2.5 and $6.964055/1M for Qwen3.8 Max. The comparison uses current catalog prices and updates as provider pricing changes.

Is MoonshotAI: Kimi K2.5 or Qwen3.8 Max faster?

Current measured p50 time to first token is not enough data for MoonshotAI: Kimi K2.5 and not enough data for Qwen3.8 Max. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MoonshotAI: Kimi K2.5 and Qwen3.8 Max 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-k2.5 and qwen/qwen3.8-max. This makes side-by-side evals possible without maintaining two provider integrations.