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Google: Gemma 4 31B vs GPT Image 2.5 Flare

Google: Gemma 4 31B vs GPT Image 2.5 Flare: 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 and more Credits provider routes. There is not enough recent probe data to compare speed.

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

$36.925/1MGPT Image 2.5 Flare cheapest route

962 msGoogle: Gemma 4 31B fastest measured p50 TTFT via friendli

not enough dataGPT Image 2.5 Flare 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 31BGPT Image 2.5 Flare

Model idgoogle/gemma-4-31b-itopenai/gpt-image-2.5-flare

Publisher Google AI Studio OpenAI

AI IQ IQ 101#99 —

Context262,144 tokens0 tokens

Credits provider routes161

Cheapest route$0.45365/1M$36.925/1M

Cached input$0.03798/1M to $0.26375/1M$1.31875/1M

Privacy posturehas provider E2EE routehas ZDR route

Fastest measured p50 TTFT962 ms via friendlinot enough data

Highest measured throughput271 tok/s via tinfoilnot enough data

Recent route uptime range50.00% to 100.00%not enough data

Modes chat

Google: Gemma 4 31B routes

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

GPT Image 2.5 Flare 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 GPT Image 2.5 Flare?

Google: Gemma 4 31B has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

Is Google: Gemma 4 31B or GPT Image 2.5 Flare cheaper?

The current cheapest TrustedRouter route is $0.45365/1M for Google: Gemma 4 31B and $36.925/1M for GPT Image 2.5 Flare. The comparison uses current catalog prices and updates as provider pricing changes.

Is Google: Gemma 4 31B or GPT Image 2.5 Flare faster?

Current measured p50 time to first token is 962 ms for Google: Gemma 4 31B and not enough data for GPT Image 2.5 Flare. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Google: Gemma 4 31B and GPT Image 2.5 Flare with the same API?

Both use the same TrustedRouter base URL and API key. At least one of them is not a chat model, so the request can differ as well as the model id: the API docs list the route for each kind of model.