OpenAI compatible API · Attested · Public status

NVIDIA: Nemotron 3.5 Lightning vs Qwen: Qwen3.8 27B

NVIDIA: Nemotron 3.5 Lightning vs Qwen: Qwen3.8 27B: 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

NVIDIA: Nemotron 3.5 Lightning has the lower published input-plus-output rate. Qwen: Qwen3.8 27B has more Credits provider routes. Their context windows are the same size. There is not enough recent probe data to compare speed.

$0.26375/1MNVIDIA: Nemotron 3.5 Lightning cheapest route
$0.385075/1MQwen: Qwen3.8 27B cheapest route
not enough dataNVIDIA: Nemotron 3.5 Lightning fastest measured p50 TTFT
1325 msQwen: Qwen3.8 27B fastest measured p50 TTFT via pearl

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: Qwen3.8 27B
Model idnvidia/nemotron-3.5-lightningqwen/qwen3.8-27b
AI IQ IQ 110#59
Context262,144 tokens262,144 tokens
Credits provider routes214
Cheapest route$0.26375/1M$0.385075/1M
Cached input$0.01055/1M to $0.0422/1M$0.015825/1M to $0.16669/1M
Privacy postureprovider posture varieshas ZDR route
Fastest measured p50 TTFTnot enough data1325 ms via pearl
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%93.75% to 100.00%
Modes chat chat

NVIDIA: Nemotron 3.5 Lightning routes

Qwen: Qwen3.8 27B 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: Qwen3.8 27B?

NVIDIA: Nemotron 3.5 Lightning has the lower published input-plus-output rate. Qwen: Qwen3.8 27B has more Credits provider routes. Their context windows are the same size. There is not enough recent probe data to compare speed.

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3.8 27B cheaper?

The current cheapest TrustedRouter route is $0.26375/1M for NVIDIA: Nemotron 3.5 Lightning and $0.385075/1M for Qwen: Qwen3.8 27B. The comparison uses current catalog prices and updates as provider pricing changes.

Is NVIDIA: Nemotron 3.5 Lightning or Qwen: Qwen3.8 27B faster?

Current measured p50 time to first token is not enough data for NVIDIA: Nemotron 3.5 Lightning and 1325 ms for Qwen: Qwen3.8 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: Qwen3.8 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/qwen3.8-27b. This makes side-by-side evals possible without maintaining two provider integrations.

Workspace access

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