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OpenAI compatible API · Attested · Public status

Meta: Muse Spark 1.2 vs MiniMax: MiniMax M3

Muse Spark 1.2 has the larger context window. MiniMax: MiniMax M3 has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token. Compare price, speed, context, and privacy.

Verify gateway
Onebase URL to migrate
100sof models and routes
0prompt or output logs. Always.
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 1.2 has the larger context window. MiniMax: MiniMax M3 has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token.

$5.8025/1MMeta: Muse Spark 1.2 cheapest route
$1.25545/1MMiniMax: MiniMax M3 cheapest route
2452 msMeta: Muse Spark 1.2 fastest measured p50 TTFT via meta
835 msMiniMax: MiniMax M3 fastest measured p50 TTFT via minimax

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 1.2MiniMax: MiniMax M3
Model idmeta/muse-spark-1.2minimax/minimax-m3
Context1,048,576 tokens524,288 tokens
Credits provider routes115
Cheapest route$5.8025/1M$1.25545/1M
Cached input$0.15825/1M$0.05275/1M to $0.2532/1M
Privacy postureprovider posture varieshas ZDR route
Fastest measured p50 TTFT2452 ms via meta835 ms via minimax
Highest measured throughputnot enough data309 tok/s via parasail
Recent route uptime range100.00%100.00%
Modes chat chat

Meta: Muse Spark 1.2 routes

MiniMax: MiniMax M3 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/muse-spark-1.2",
    messages=messages,
)

Questions

Which should I use, Meta: Muse Spark 1.2 or MiniMax: MiniMax M3?

Muse Spark 1.2 has the larger context window. MiniMax: MiniMax M3 has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token.

Is Meta: Muse Spark 1.2 or MiniMax: MiniMax M3 cheaper?

The current cheapest TrustedRouter route is $5.8025/1M for Meta: Muse Spark 1.2 and $1.25545/1M for MiniMax: MiniMax M3. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Muse Spark 1.2 or MiniMax: MiniMax M3 faster?

Current measured p50 time to first token is 2452 ms for Meta: Muse Spark 1.2 and 835 ms for MiniMax: MiniMax M3. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Meta: Muse Spark 1.2 and MiniMax: MiniMax M3 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-1.2 and minimax/minimax-m3. This makes side-by-side evals possible without maintaining two provider integrations.

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