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NVIDIA: Nemotron 3.5 Lightning vs Qwen: Qwen3 Next 80B A3B Instruct

Try both on us. Starter credit covers your first requests, then one key routes Nemotron 3.5 Lightning and Qwen3 Next 80B A3B Instruct. 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 and the lower measured p50 time to first token. Qwen: Qwen3 Next 80B A3B Instruct has more Credits provider routes. Their context windows are the same size.

$0.223309/1MNVIDIA: Nemotron 3.5 Lightning cheapest route
$1.25545/1MQwen: Qwen3 Next 80B A3B Instruct cheapest route
841 msNVIDIA: Nemotron 3.5 Lightning fastest measured p50 TTFT via io-net
1893 msQwen: Qwen3 Next 80B A3B Instruct fastest measured p50 TTFT via databricks

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 Next 80B A3B Instruct
Model idnvidia/nemotron-3.5-lightningqwen/qwen3-next-80b-a3b-instruct
AI IQ — —
Context262,144 tokens262,144 tokens
Credits provider routes35
Cheapest route$0.223309/1M$1.25545/1M
Cached input$0.01055/1M to $0.03165/1M$0.062641/1M to $0.07385/1M
Privacy postureprovider posture varieshas ZDR route
Fastest measured p50 TTFT841 ms via io-net1893 ms via databricks
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%100.00%
Modes chat chat

NVIDIA: Nemotron 3.5 Lightning routes

Qwen: Qwen3 Next 80B A3B Instruct 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="nvidia/nemotron-3.5-lightning",
    messages=messages,
)

Questions

Which should I use, NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3 Next 80B A3B Instruct?

NVIDIA: Nemotron 3.5 Lightning has the lower published input-plus-output rate and the lower measured p50 time to first token. Qwen: Qwen3 Next 80B A3B Instruct has more Credits provider routes. Their context windows are the same size.

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3 Next 80B A3B Instruct cheaper?

The current cheapest TrustedRouter route is $0.223309/1M for NVIDIA: Nemotron 3.5 Lightning and $1.25545/1M for Qwen: Qwen3 Next 80B A3B Instruct. The comparison uses current catalog prices and updates as provider pricing changes.

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3 Next 80B A3B Instruct faster?

Current measured p50 time to first token is 841 ms for NVIDIA: Nemotron 3.5 Lightning and 1893 ms for Qwen: Qwen3 Next 80B A3B Instruct. 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 Next 80B A3B Instruct 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-next-80b-a3b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.

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