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Qwen/Qwen3-235B-A22B-Instruct-2507 vs Z.ai: GLM 4.7 Flash

Try both on us. Starter credit covers your first requests, then one key routes Qwen/Qwen3-235B-A22B-Instruct-2507 and GLM 4.7 Flash. 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/Qwen3-235B-A22B-Instruct-2507 has the larger context window. Z.ai: GLM 4.7 Flash has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

$0.6752/1MQwen/Qwen3-235B-A22B-Instruct-2507 cheapest route

$0.4853/1MZ.ai: GLM 4.7 Flash cheapest route

not enough dataQwen/Qwen3-235B-A22B-Instruct-2507 fastest measured p50 TTFT

not enough dataZ.ai: GLM 4.7 Flash 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.

Qwen/Qwen3-235B-A22B-Instruct-2507Z.ai: GLM 4.7 Flash

Model idqwen/qwen3-235b-a22b-instruct-2507z-ai/glm-4.7-flash

Publisher Alibaba Cloud Model Studio Z.AI

AI IQ — —

Context262,144 tokens131,072 tokens

Credits provider routes45

Cheapest route$0.6752/1M$0.4853/1M

Cached inputNot published$0.01055/1M to $0.03442/1M

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

Qwen/Qwen3-235B-A22B-Instruct-2507 routes

Overview4 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Z.ai: GLM 4.7 Flash routes

Overview5 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

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Z.ai: GLM 4.7 Flash vs Z.ai: GLM 5.338 combined provider routes
Qwen/Qwen3-235B-A22B-Instruct-2507 vs Z.ai: GLM 5.337 combined provider routes
Z.ai: GLM 4.7 Flash vs Z.ai: GLM 5.237 combined provider routes
Z.ai: GLM 4.7 Flash vs Z.ai: GLM 5.3 Flash37 combined provider routes
Qwen/Qwen3-235B-A22B-Instruct-2507 vs Z.ai: GLM 5.236 combined provider routes
Qwen/Qwen3-235B-A22B-Instruct-2507 vs Z.ai: GLM 5.3 Flash36 combined provider routes
MoonshotAI: Kimi K3 vs Z.ai: GLM 4.7 Flash33 combined provider routes
MoonshotAI: Kimi K3 vs Qwen/Qwen3-235B-A22B-Instruct-250732 combined provider routes

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="qwen/qwen3-235b-a22b-instruct-2507",
    messages=messages,
)

Questions

Which should I use, Qwen/Qwen3-235B-A22B-Instruct-2507 or Z.ai: GLM 4.7 Flash?

Is Qwen/Qwen3-235B-A22B-Instruct-2507 or Z.ai: GLM 4.7 Flash cheaper?

The current cheapest TrustedRouter route is $0.6752/1M for Qwen/Qwen3-235B-A22B-Instruct-2507 and $0.4853/1M for Z.ai: GLM 4.7 Flash. The comparison uses current catalog prices and updates as provider pricing changes.

Is Qwen/Qwen3-235B-A22B-Instruct-2507 or Z.ai: GLM 4.7 Flash faster?

Current measured p50 time to first token is not enough data for Qwen/Qwen3-235B-A22B-Instruct-2507 and not enough data for Z.ai: GLM 4.7 Flash. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Qwen/Qwen3-235B-A22B-Instruct-2507 and Z.ai: GLM 4.7 Flash with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between qwen/qwen3-235b-a22b-instruct-2507 and z-ai/glm-4.7-flash. This makes side-by-side evals possible without maintaining two provider integrations.