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Llama 4 Scout Instruct vs Qwen: Qwen3.5-27B

Try both on us. Starter credit covers your first requests, then one key routes Llama 4 Scout Instruct and Qwen3.5-27B. 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. Qwen: Qwen3.5-27B has 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
$2.56365/1MQwen: Qwen3.5-27B cheapest route
not enough dataLlama 4 Scout Instruct fastest measured p50 TTFT
not enough dataQwen: Qwen3.5-27B 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: Qwen3.5-27B
Model idmeta-llama/llama-4-scout-17b-16e-instructqwen/qwen3.5-27b
AI IQ — —
Context131,072 tokens262,144 tokens
Credits provider routes35
Cheapest route$0.422/1M$2.56365/1M
Cached inputNot published$0.03165/1M to $0.28485/1M
Privacy postureprovider posture variesprovider posture varies
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

Qwen: Qwen3.5-27B 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-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: Qwen3.5-27B?

Llama 4 Scout Instruct has the lower published input-plus-output rate. Qwen: Qwen3.5-27B has 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: Qwen3.5-27B cheaper?

The current cheapest TrustedRouter route is $0.422/1M for Llama 4 Scout Instruct and $2.56365/1M for Qwen: Qwen3.5-27B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Llama 4 Scout Instruct or Qwen: Qwen3.5-27B faster?

Current measured p50 time to first token is not enough data for Llama 4 Scout Instruct and not enough data for Qwen: Qwen3.5-27B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Llama 4 Scout Instruct and Qwen: Qwen3.5-27B 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/qwen3.5-27b. This makes side-by-side evals possible without maintaining two provider integrations.

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