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Llama 4 Scout Instruct vs MoonshotAI: Kimi K2.7 Code

Try both on us. Starter credit covers your first requests, then one key routes Llama 4 Scout Instruct and Kimi K2.7 Code. 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

Llama 4 Scout Instruct has the lower published input-plus-output rate. MoonshotAI: Kimi K2.7 Code has more Credits provider routes, the larger context window and the lower measured p50 time to first token.

$0.422/1MLlama 4 Scout Instruct cheapest route
$4.173791/1MMoonshotAI: Kimi K2.7 Code cheapest route
2387 msLlama 4 Scout Instruct fastest measured p50 TTFT via cloudflare-workers-ai
1678 msMoonshotAI: Kimi K2.7 Code fastest measured p50 TTFT via wandb

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.

Llama 4 Scout InstructMoonshotAI: Kimi K2.7 Code
Model idmeta-llama/llama-4-scout-17b-16e-instructmoonshotai/kimi-k2.7-code
Publisher Meta Kimi
AI IQ — IQ 111#77
Context131,072 tokens262,144 tokens
Credits provider routes314
Cheapest route$0.422/1M$4.173791/1M
Cached inputNot published$0.15825/1M to $0.546617/1M
Privacy postureprovider posture varieshas ZDR route
Fastest measured p50 TTFT2387 ms via cloudflare-workers-ai1678 ms via wandb
Highest measured throughputnot enough data167 tok/s via lyceum
Recent route uptime range0.00% to 100.00%100.00%
Modes chat chat

Llama 4 Scout Instruct routes

MoonshotAI: Kimi K2.7 Code 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="meta-llama/llama-4-scout-17b-16e-instruct",
    messages=messages,
)

Questions

Which should I use, Llama 4 Scout Instruct or MoonshotAI: Kimi K2.7 Code?

Llama 4 Scout Instruct has the lower published input-plus-output rate. MoonshotAI: Kimi K2.7 Code has more Credits provider routes, the larger context window and the lower measured p50 time to first token.

Is Llama 4 Scout Instruct or MoonshotAI: Kimi K2.7 Code cheaper?

The current cheapest TrustedRouter route is $0.422/1M for Llama 4 Scout Instruct and $4.173791/1M for MoonshotAI: Kimi K2.7 Code. The comparison uses current catalog prices and updates as provider pricing changes.

Is Llama 4 Scout Instruct or MoonshotAI: Kimi K2.7 Code faster?

Current measured p50 time to first token is 2387 ms for Llama 4 Scout Instruct and 1678 ms for MoonshotAI: Kimi K2.7 Code. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Llama 4 Scout Instruct and MoonshotAI: Kimi K2.7 Code with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/llama-4-scout-17b-16e-instruct and moonshotai/kimi-k2.7-code. This makes side-by-side evals possible without maintaining two provider integrations.

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