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DeepSeek: DeepSeek V4 Flash 0731 vs Meta: Muse Spark 1.2

Try both on us. Starter credit covers your first requests, then one key routes DeepSeek V4 Flash 0731 and Muse Spark 1.2. 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 V4 Flash 0731 has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token. Their context windows are the same size.

$0.142425/1MDeepSeek: DeepSeek V4 Flash 0731 cheapest route

$5.8025/1MMeta: Muse Spark 1.2 cheapest route

841 msDeepSeek: DeepSeek V4 Flash 0731 fastest measured p50 TTFT via boundless

1751 msMeta: Muse Spark 1.2 fastest measured p50 TTFT via meta

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: DeepSeek V4 Flash 0731Meta: Muse Spark 1.2

Model iddeepseek/deepseek-v4-flash-0731meta/muse-spark-1.2

Publisher DeepSeek Meta

AI IQ — IQ 121#42

Context1,048,576 tokens1,048,576 tokens

Credits provider routes261

Cheapest route$0.142425/1M$5.8025/1M

Cached input$0.01/1M to $0.118793/1M$0.15825/1M

Privacy posturehas Confidential route (E2EE + ZDR)provider posture varies

Fastest measured p50 TTFT841 ms via boundless1751 ms via meta

Highest measured throughput171 tok/s via confidential-ainot enough data

Recent route uptime range66.67% to 100.00%100.00%

Modes chat chat

DeepSeek: DeepSeek V4 Flash 0731 routes

Overview26 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Meta: Muse Spark 1.2 routes

Overview1 Credits 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="deepseek/deepseek-v4-flash-0731",
    messages=messages,
)

Questions

Which should I use, DeepSeek: DeepSeek V4 Flash 0731 or Meta: Muse Spark 1.2?

DeepSeek V4 Flash 0731 has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token. Their context windows are the same size.

Is DeepSeek: DeepSeek V4 Flash 0731 or Meta: Muse Spark 1.2 cheaper?

The current cheapest TrustedRouter route is $0.142425/1M for DeepSeek: DeepSeek V4 Flash 0731 and $5.8025/1M for Meta: Muse Spark 1.2. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek: DeepSeek V4 Flash 0731 or Meta: Muse Spark 1.2 faster?

Current measured p50 time to first token is 841 ms for DeepSeek: DeepSeek V4 Flash 0731 and 1751 ms for Meta: Muse Spark 1.2. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test DeepSeek: DeepSeek V4 Flash 0731 and Meta: Muse Spark 1.2 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-v4-flash-0731 and meta/muse-spark-1.2. This makes side-by-side evals possible without maintaining two provider integrations.