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NVIDIA: Nemotron 3.5 Super VL vs Qwen: Qwen3.8 2.4T A95B

Try both on us. Starter credit covers your first requests, then one key routes Nemotron 3.5 Super VL and Qwen3.8 2.4T A95B. 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 Super VL has the lower published input-plus-output rate and the larger context window. Qwen: Qwen3.8 2.4T A95B has more Credits provider routes and the lower measured p50 time to first token.

$0.5275/1MNVIDIA: Nemotron 3.5 Super VL cheapest route
$5.275/1MQwen: Qwen3.8 2.4T A95B cheapest route
1400 msNVIDIA: Nemotron 3.5 Super VL fastest measured p50 TTFT via io-net
1089 msQwen: Qwen3.8 2.4T A95B fastest measured p50 TTFT via together

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 Super VLQwen: Qwen3.8 2.4T A95B
Model idnvidia/nemotron-3.5-super-vlqwen/qwen3.8-2.4t-a95b
Context1,048,576 tokens1,000,000 tokens
Credits provider routes46
Cheapest route$0.5275/1M$5.275/1M
Cached input$0.0211/1M to $0.089675/1M$0.26375/1M to $0.66465/1M
Privacy posturehas ZDR routehas ZDR route
Fastest measured p50 TTFT1400 ms via io-net1089 ms via together
Highest measured throughputnot enough datanot enough data
Recent route uptime range50.00% to 100.00%100.00%
Modes chat chat

NVIDIA: Nemotron 3.5 Super VL routes

Qwen: Qwen3.8 2.4T A95B 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-super-vl",
    messages=messages,
)

Questions

Which should I use, NVIDIA: Nemotron 3.5 Super VL or Qwen: Qwen3.8 2.4T A95B?

NVIDIA: Nemotron 3.5 Super VL has the lower published input-plus-output rate and the larger context window. Qwen: Qwen3.8 2.4T A95B has more Credits provider routes and the lower measured p50 time to first token.

Is NVIDIA: Nemotron 3.5 Super VL or Qwen: Qwen3.8 2.4T A95B cheaper?

The current cheapest TrustedRouter route is $0.5275/1M for NVIDIA: Nemotron 3.5 Super VL and $5.275/1M for Qwen: Qwen3.8 2.4T A95B. The comparison uses current catalog prices and updates as provider pricing changes.

Is NVIDIA: Nemotron 3.5 Super VL or Qwen: Qwen3.8 2.4T A95B faster?

Current measured p50 time to first token is 1400 ms for NVIDIA: Nemotron 3.5 Super VL and 1089 ms for Qwen: Qwen3.8 2.4T A95B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test NVIDIA: Nemotron 3.5 Super VL and Qwen: Qwen3.8 2.4T A95B 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-super-vl and qwen/qwen3.8-2.4t-a95b. This makes side-by-side evals possible without maintaining two provider integrations.

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