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Google: Gemma 4 31B vs nvidia/Nemotron-3.5-Lightning-30B-A3B

Try both on us. Starter credit covers your first requests, then one key routes Gemma 4 31B and nvidia/Nemotron-3.5-Lightning-30B-A3B. 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

Google: Gemma 4 31B has more Credits provider routes and the lower measured p50 time to first token. nvidia/Nemotron-3.5-Lightning-30B-A3B has the lower published input-plus-output rate. Their context windows are the same size.

$0.45365/1MGoogle: Gemma 4 31B cheapest route
$0.26375/1Mnvidia/Nemotron-3.5-Lightning-30B-A3B cheapest route
665 msGoogle: Gemma 4 31B fastest measured p50 TTFT via crusoe
812 msnvidia/Nemotron-3.5-Lightning-30B-A3B fastest measured p50 TTFT via nvidia-nim

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 31Bnvidia/Nemotron-3.5-Lightning-30B-A3B
Model idgoogle/gemma-4-31b-itnvidia/nemotron-3.5-lightning-30b-a3b
Publisher Google AI Studio NVIDIA
AI IQ IQ 101#116 —
Context262,144 tokens262,144 tokens
Credits provider routes163
Cheapest route$0.45365/1M$0.26375/1M
Cached input$0.03798/1M to $0.26375/1M$0.03165/1M to $0.0422/1M
Privacy posturehas Confidential route (E2EE + ZDR)provider posture varies
Fastest measured p50 TTFT665 ms via crusoe812 ms via nvidia-nim
Highest measured throughput146 tok/s via crusoenot enough data
Recent route uptime range0.00% to 100.00%100.00%
Modes chat chat

Google: Gemma 4 31B routes

nvidia/Nemotron-3.5-Lightning-30B-A3B 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 nvidia/Nemotron-3.5-Lightning-30B-A3B?

Google: Gemma 4 31B has more Credits provider routes and the lower measured p50 time to first token. nvidia/Nemotron-3.5-Lightning-30B-A3B has the lower published input-plus-output rate. Their context windows are the same size.

Is Google: Gemma 4 31B or nvidia/Nemotron-3.5-Lightning-30B-A3B cheaper?

The current cheapest TrustedRouter route is $0.45365/1M for Google: Gemma 4 31B and $0.26375/1M for nvidia/Nemotron-3.5-Lightning-30B-A3B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Google: Gemma 4 31B or nvidia/Nemotron-3.5-Lightning-30B-A3B faster?

Current measured p50 time to first token is 665 ms for Google: Gemma 4 31B and 812 ms for nvidia/Nemotron-3.5-Lightning-30B-A3B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Google: Gemma 4 31B and nvidia/Nemotron-3.5-Lightning-30B-A3B 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 nvidia/nemotron-3.5-lightning-30b-a3b. This makes side-by-side evals possible without maintaining two provider integrations.

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