OpenAI compatible API · Attested · Public status

DeepSeek: DeepSeek V3.2 Exp vs Google: Gemma 4 31B

DeepSeek V3.2 Exp vs Google: Gemma 4 31B: 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.

$0.7174/1MDeepSeek: DeepSeek V3.2 Exp cheapest route
$0.45365/1MGoogle: Gemma 4 31B cheapest route
not enough dataDeepSeek: DeepSeek V3.2 Exp fastest measured p50 TTFT
1179 msGoogle: Gemma 4 31B fastest measured p50 TTFT via lightning

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.

DeepSeek: DeepSeek V3.2 ExpGoogle: Gemma 4 31B
Model iddeepseek/deepseek-v3.2-expgoogle/gemma-4-31b-it
AI IQ IQ 103#79
Context163,840 tokens262,144 tokens
Credits provider routes215
Cheapest route$0.7174/1M$0.45365/1M
Cached input$0.28485/1M$0.03798/1M to $0.211/1M
Privacy postureprovider posture varieshas provider E2EE route
Fastest measured p50 TTFTnot enough data1179 ms via lightning
Highest measured throughputnot enough datanot enough data
Recent route uptime rangenot enough data0.00% to 100.00%
Modes chat chat

DeepSeek: DeepSeek V3.2 Exp routes

Google: Gemma 4 31B routes

Related comparisons

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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="deepseek/deepseek-v3.2-exp",
    messages=messages,
)

Questions

Which should I use, DeepSeek: DeepSeek V3.2 Exp or Google: Gemma 4 31B?

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 DeepSeek: DeepSeek V3.2 Exp or Google: Gemma 4 31B cheaper?

The current cheapest TrustedRouter route is $0.7174/1M for DeepSeek: DeepSeek V3.2 Exp and $0.45365/1M for Google: Gemma 4 31B. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek: DeepSeek V3.2 Exp or Google: Gemma 4 31B faster?

Current measured p50 time to first token is not enough data for DeepSeek: DeepSeek V3.2 Exp and 1179 ms for Google: Gemma 4 31B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test DeepSeek: DeepSeek V3.2 Exp and Google: Gemma 4 31B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between deepseek/deepseek-v3.2-exp and google/gemma-4-31b-it. This makes side-by-side evals possible without maintaining two provider integrations.

Workspace access

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