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NVIDIA: Nemotron 3.5 Lightning vs Qwen: Qwen3.5-27B

Try both on us. Starter credit covers your first requests, then one key routes Nemotron 3.5 Lightning and Qwen3.5-27B. 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

NVIDIA: Nemotron 3.5 Lightning has the lower published input-plus-output rate. Qwen: Qwen3.5-27B has more Credits provider routes. Their context windows are the same size. There is not enough recent probe data to compare speed.

$0.223309/1MNVIDIA: Nemotron 3.5 Lightning cheapest route

$2.56365/1MQwen: Qwen3.5-27B cheapest route

not enough dataNVIDIA: Nemotron 3.5 Lightning fastest measured p50 TTFT

not enough dataQwen: Qwen3.5-27B 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.

NVIDIA: Nemotron 3.5 LightningQwen: Qwen3.5-27B

Model idnvidia/nemotron-3.5-lightningqwen/qwen3.5-27b

PublisherNVIDIA Alibaba Cloud Model Studio

AI IQ — —

Context262,144 tokens262,144 tokens

Credits provider routes35

Cheapest route$0.223309/1M$2.56365/1M

Cached input$0.01055/1M to $0.03165/1M$0.03165/1M to $0.28485/1M

Privacy postureprovider posture variesprovider posture varies

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

NVIDIA: Nemotron 3.5 Lightning routes

Overview3 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Qwen: Qwen3.5-27B routes

Overview5 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

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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="nvidia/nemotron-3.5-lightning",
    messages=messages,
)

Questions

Which should I use, NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3.5-27B?

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3.5-27B cheaper?

The current cheapest TrustedRouter route is $0.223309/1M for NVIDIA: Nemotron 3.5 Lightning and $2.56365/1M for Qwen: Qwen3.5-27B. The comparison uses current catalog prices and updates as provider pricing changes.

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3.5-27B faster?

Current measured p50 time to first token is not enough data for NVIDIA: Nemotron 3.5 Lightning and not enough data for Qwen: Qwen3.5-27B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test NVIDIA: Nemotron 3.5 Lightning and Qwen: Qwen3.5-27B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between nvidia/nemotron-3.5-lightning and qwen/qwen3.5-27b. This makes side-by-side evals possible without maintaining two provider integrations.