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Llama 4 Scout Instruct vs Z.ai: GLM 5.3

Try both on us. Starter credit covers your first requests, then one key routes Llama 4 Scout Instruct and GLM 5.3. 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. Z.ai: GLM 5.3 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

$3.458818/1MZ.ai: GLM 5.3 cheapest route

not enough dataLlama 4 Scout Instruct fastest measured p50 TTFT

not enough dataZ.ai: GLM 5.3 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 InstructZ.ai: GLM 5.3

Model idmeta-llama/llama-4-scout-17b-16e-instructz-ai/glm-5.3

Publisher Meta Z.AI

AI IQ — IQ 124#28

Context131,072 tokens1,048,576 tokens

Credits provider routes333

Cheapest route$0.422/1M$3.458818/1M

Cached inputNot published$0.1055/1M to $0.84189/1M

Privacy postureprovider posture varieshas Confidential route (E2EE + ZDR)

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

Z.ai: GLM 5.3 routes

Overview33 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 Z.ai: GLM 5.3?

Is Llama 4 Scout Instruct or Z.ai: GLM 5.3 cheaper?

The current cheapest TrustedRouter route is $0.422/1M for Llama 4 Scout Instruct and $3.458818/1M for Z.ai: GLM 5.3. The comparison uses current catalog prices and updates as provider pricing changes.

Is Llama 4 Scout Instruct or Z.ai: GLM 5.3 faster?

Current measured p50 time to first token is not enough data for Llama 4 Scout Instruct and not enough data for Z.ai: GLM 5.3. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Llama 4 Scout Instruct and Z.ai: GLM 5.3 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 z-ai/glm-5.3. This makes side-by-side evals possible without maintaining two provider integrations.