OpenAI compatible API · Attested · Public status

Google: Gemma 4 31B vs GLM 4.6V

Google: Gemma 4 31B vs GLM 4.6V: compare current API pricing, context, provider routes, privacy, p50 latency, and OpenAI-compatible access.

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

Google: Gemma 4 31B 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.

$0.45365/1MGoogle: Gemma 4 31B cheapest route

$1.266/1MGLM 4.6V cheapest route

642 msGoogle: Gemma 4 31B fastest measured p50 TTFT via sail-research

not enough dataGLM 4.6V 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.

Google: Gemma 4 31BGLM 4.6V

Model idgoogle/gemma-4-31b-itzai-org/glm-4.6v

Publisher Google AI Studio Novita AI

AI IQ IQ 101#100 —

Context262,144 tokens131,072 tokens

Credits provider routes161

Cheapest route$0.45365/1M$1.266/1M

Cached input$0.03798/1M to $0.26375/1M$0.058025/1M

Privacy posturehas provider E2EE routeprovider posture varies

Fastest measured p50 TTFT642 ms via sail-researchnot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime range40.00% to 100.00%100.00%

Modes chat chat

Google: Gemma 4 31B routes

Overview16 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

GLM 4.6V routes

Overview1 Credits 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="google/gemma-4-31b-it",
    messages=messages,
)

Questions

Which should I use, Google: Gemma 4 31B or GLM 4.6V?

Google: Gemma 4 31B 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 Google: Gemma 4 31B or GLM 4.6V cheaper?

The current cheapest TrustedRouter route is $0.45365/1M for Google: Gemma 4 31B and $1.266/1M for GLM 4.6V. The comparison uses current catalog prices and updates as provider pricing changes.

Is Google: Gemma 4 31B or GLM 4.6V faster?

Current measured p50 time to first token is 642 ms for Google: Gemma 4 31B and not enough data for GLM 4.6V. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Google: Gemma 4 31B and GLM 4.6V with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between google/gemma-4-31b-it and zai-org/glm-4.6v. This makes side-by-side evals possible without maintaining two provider integrations.