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devstral-2-123b vs MoonshotAI: Kimi K2.6

Try both on us. Starter credit covers your first requests, then one key routes devstral-2-123b and Kimi K2.6. 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 K2.6 has more Credits provider routes and the larger context window. The lowest published input-plus-output rates are equal. There is not enough recent probe data to compare speed.

$2.532/1Mdevstral-2-123b cheapest route

$2.532/1MMoonshotAI: Kimi K2.6 cheapest route

not enough datadevstral-2-123b fastest measured p50 TTFT

1087 msMoonshotAI: Kimi K2.6 fastest measured p50 TTFT via sail-research

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.

devstral-2-123bMoonshotAI: Kimi K2.6

Model idmistralai/devstral-2-123bmoonshotai/kimi-k2.6

Publisher Mistral Kimi

AI IQ — IQ 114#58

Context4,096 tokens262,144 tokens

Credits provider routes117

Cheapest route$2.532/1M$2.532/1M

Cached inputNot published$0.047475/1M to $0.422/1M

Privacy postureprovider posture varieshas Confidential route (E2EE + ZDR)

Fastest measured p50 TTFTnot enough data1087 ms via sail-research

Highest measured throughputnot enough data57 tok/s via telnyx

Recent route uptime rangenot enough data100.00%

Modes chat chat

devstral-2-123b routes

Overview1 Credits routes

MoonshotAI: Kimi K2.6 routes

Overview17 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
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.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="mistralai/devstral-2-123b",
    messages=messages,
)

Questions

Which should I use, devstral-2-123b or MoonshotAI: Kimi K2.6?

MoonshotAI: Kimi K2.6 has more Credits provider routes and the larger context window. The lowest published input-plus-output rates are equal. There is not enough recent probe data to compare speed.

Is devstral-2-123b or MoonshotAI: Kimi K2.6 cheaper?

The current cheapest TrustedRouter route is $2.532/1M for devstral-2-123b and $2.532/1M for MoonshotAI: Kimi K2.6. The comparison uses current catalog prices and updates as provider pricing changes.

Is devstral-2-123b or MoonshotAI: Kimi K2.6 faster?

Current measured p50 time to first token is not enough data for devstral-2-123b and 1087 ms for MoonshotAI: Kimi K2.6. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test devstral-2-123b and MoonshotAI: Kimi K2.6 with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between mistralai/devstral-2-123b and moonshotai/kimi-k2.6. This makes side-by-side evals possible without maintaining two provider integrations.