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Google: Gemma 3 27B vs NVIDIA: Nemotron 3 Ultra

Try both on us. Starter credit covers your first requests, then one key routes Gemma 3 27B and Nemotron 3 Ultra. 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 3 27B has the lower published input-plus-output rate. NVIDIA: Nemotron 3 Ultra has the larger context window. Both have 5 Credits provider routes. There is not enough recent probe data to compare speed.

$0.2532/1MGoogle: Gemma 3 27B cheapest route
$2.79575/1MNVIDIA: Nemotron 3 Ultra cheapest route
not enough dataGoogle: Gemma 3 27B fastest measured p50 TTFT
not enough dataNVIDIA: Nemotron 3 Ultra 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 3 27BNVIDIA: Nemotron 3 Ultra
Model idgoogle/gemma-3-27b-itnvidia/nemotron-3-ultra-550b-a55b
Publisher Google AI Studio NVIDIA
AI IQ — —
Context131,072 tokens262,144 tokens
Credits provider routes55
Cheapest route$0.2532/1M$2.79575/1M
Cached input$0.0422/1M$0.1055/1M to $0.1266/1M
Privacy posturehas ZDR routehas 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

Google: Gemma 3 27B routes

NVIDIA: Nemotron 3 Ultra 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-azure.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="google/gemma-3-27b-it",
    messages=messages,
)

Questions

Which should I use, Google: Gemma 3 27B or NVIDIA: Nemotron 3 Ultra?

Google: Gemma 3 27B has the lower published input-plus-output rate. NVIDIA: Nemotron 3 Ultra has the larger context window. Both have 5 Credits provider routes. There is not enough recent probe data to compare speed.

Is Google: Gemma 3 27B or NVIDIA: Nemotron 3 Ultra cheaper?

The current cheapest TrustedRouter route is $0.2532/1M for Google: Gemma 3 27B and $2.79575/1M for NVIDIA: Nemotron 3 Ultra. The comparison uses current catalog prices and updates as provider pricing changes.

Is Google: Gemma 3 27B or NVIDIA: Nemotron 3 Ultra faster?

Current measured p50 time to first token is not enough data for Google: Gemma 3 27B and not enough data for NVIDIA: Nemotron 3 Ultra. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Google: Gemma 3 27B and NVIDIA: Nemotron 3 Ultra 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-3-27b-it and nvidia/nemotron-3-ultra-550b-a55b. This makes side-by-side evals possible without maintaining two provider integrations.

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