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Meta: Muse Spark 1.1 vs MoonshotAI: Kimi K2.7 Code

Try both on us. Starter credit covers your first requests, then one key routes Muse Spark 1.1 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

Muse Spark 1.1 has the larger context window and the lower measured p50 time to first token. MoonshotAI: Kimi K2.7 Code has the lower published input-plus-output rate and more Credits provider routes.

$5.8025/1MMeta: Muse Spark 1.1 cheapest route

$4.173791/1MMoonshotAI: Kimi K2.7 Code cheapest route

1657 msMeta: Muse Spark 1.1 fastest measured p50 TTFT via meta

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.

Meta: Muse Spark 1.1MoonshotAI: Kimi K2.7 Code

Model idmeta/muse-spark-1.1moonshotai/kimi-k2.7-code

Publisher Meta Kimi

AI IQ IQ 119#52 IQ 111#77

Context1,048,576 tokens262,144 tokens

Credits provider routes114

Cheapest route$5.8025/1M$4.173791/1M

Cached input$0.15825/1M$0.15825/1M to $0.546617/1M

Privacy postureprovider posture varieshas ZDR route

Fastest measured p50 TTFT1657 ms via meta1678 ms via wandb

Highest measured throughputnot enough data167 tok/s via lyceum

Recent route uptime range100.00%100.00%

Modes chat chat

Meta: Muse Spark 1.1 routes

Overview1 Credits routes

MoonshotAI: Kimi K2.7 Code routes

Overview14 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="meta/muse-spark-1.1",
    messages=messages,
)

Questions

Which should I use, Meta: Muse Spark 1.1 or MoonshotAI: Kimi K2.7 Code?

Is Meta: Muse Spark 1.1 or MoonshotAI: Kimi K2.7 Code cheaper?

The current cheapest TrustedRouter route is $5.8025/1M for Meta: Muse Spark 1.1 and $4.173791/1M for MoonshotAI: Kimi K2.7 Code. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Muse Spark 1.1 or MoonshotAI: Kimi K2.7 Code faster?

Current measured p50 time to first token is 1657 ms for Meta: Muse Spark 1.1 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 Meta: Muse Spark 1.1 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/muse-spark-1.1 and moonshotai/kimi-k2.7-code. This makes side-by-side evals possible without maintaining two provider integrations.