Free to start

Llama 4 Scout Instruct vs Qwen: Qwen3.5-9B

Try both on us. Starter credit covers your first requests, then one key routes Llama 4 Scout Instruct and Qwen3.5-9B. 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

Qwen: Qwen3.5-9B has the lower published input-plus-output rate, more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

$0.422/1MLlama 4 Scout Instruct cheapest route

$0.110775/1MQwen: Qwen3.5-9B cheapest route

not enough dataLlama 4 Scout Instruct fastest measured p50 TTFT

not enough dataQwen: Qwen3.5-9B fastest measured p50 TTFT

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 InstructQwen: Qwen3.5-9B

Model idmeta-llama/llama-4-scout-17b-16e-instructqwen/qwen3.5-9b

Publisher Meta Alibaba Cloud Model Studio

AI IQ — IQ 96#139

Context131,072 tokens262,144 tokens

Credits provider routes37

Cheapest route$0.422/1M$0.110775/1M

Cached inputNot published$0.0211/1M

Privacy postureprovider posture varieshas ZDR route

Fastest measured p50 TTFTnot enough datanot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime rangenot enough datanot enough data

Modes chat chat

Llama 4 Scout Instruct routes

Overview3 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Qwen: Qwen3.5-9B routes

Overview7 Credits routes
PricingInput, cached input, and output rates
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-azure.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 Qwen: Qwen3.5-9B?

Qwen: Qwen3.5-9B has the lower published input-plus-output rate, more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

Is Llama 4 Scout Instruct or Qwen: Qwen3.5-9B cheaper?

The current cheapest TrustedRouter route is $0.422/1M for Llama 4 Scout Instruct and $0.110775/1M for Qwen: Qwen3.5-9B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Llama 4 Scout Instruct or Qwen: Qwen3.5-9B faster?

Current measured p50 time to first token is not enough data for Llama 4 Scout Instruct and not enough data for Qwen: Qwen3.5-9B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Llama 4 Scout Instruct and Qwen: Qwen3.5-9B 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 qwen/qwen3.5-9b. This makes side-by-side evals possible without maintaining two provider integrations.