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DeepSeek: DeepSeek V4 Pro 0423 vs NVIDIA: Nemotron 3.5 Super VL

Try both on us. Starter credit covers your first requests, then one key routes DeepSeek V4 Pro 0423 and Nemotron 3.5 Super VL. 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

DeepSeek V4 Pro 0423 has more Credits provider routes. NVIDIA: Nemotron 3.5 Super VL has the lower published input-plus-output rate and the lower measured p50 time to first token. Their context windows are the same size.

$0.79125/1MDeepSeek: DeepSeek V4 Pro 0423 cheapest route
$0.5275/1MNVIDIA: Nemotron 3.5 Super VL cheapest route
1436 msDeepSeek: DeepSeek V4 Pro 0423 fastest measured p50 TTFT via streamlake
1400 msNVIDIA: Nemotron 3.5 Super VL fastest measured p50 TTFT via io-net

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.

DeepSeek: DeepSeek V4 Pro 0423NVIDIA: Nemotron 3.5 Super VL
Model iddeepseek/deepseek-v4-pronvidia/nemotron-3.5-super-vl
Publisher DeepSeek NVIDIA
Context1,048,576 tokens1,048,576 tokens
Credits provider routes144
Cheapest route$0.79125/1M$0.5275/1M
Cached input$0.01/1M to $0.74905/1M$0.0211/1M to $0.089675/1M
Privacy posturehas ZDR routehas ZDR route
Fastest measured p50 TTFT1436 ms via streamlake1400 ms via io-net
Highest measured throughputnot enough datanot enough data
Recent route uptime range66.67% to 100.00%50.00% to 100.00%
Modes chat chat

DeepSeek: DeepSeek V4 Pro 0423 routes

NVIDIA: Nemotron 3.5 Super VL 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="deepseek/deepseek-v4-pro",
    messages=messages,
)

Questions

Which should I use, DeepSeek: DeepSeek V4 Pro 0423 or NVIDIA: Nemotron 3.5 Super VL?

DeepSeek V4 Pro 0423 has more Credits provider routes. NVIDIA: Nemotron 3.5 Super VL has the lower published input-plus-output rate and the lower measured p50 time to first token. Their context windows are the same size.

Is DeepSeek: DeepSeek V4 Pro 0423 or NVIDIA: Nemotron 3.5 Super VL cheaper?

The current cheapest TrustedRouter route is $0.79125/1M for DeepSeek: DeepSeek V4 Pro 0423 and $0.5275/1M for NVIDIA: Nemotron 3.5 Super VL. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek: DeepSeek V4 Pro 0423 or NVIDIA: Nemotron 3.5 Super VL faster?

Current measured p50 time to first token is 1436 ms for DeepSeek: DeepSeek V4 Pro 0423 and 1400 ms for NVIDIA: Nemotron 3.5 Super VL. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test DeepSeek: DeepSeek V4 Pro 0423 and NVIDIA: Nemotron 3.5 Super VL with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between deepseek/deepseek-v4-pro and nvidia/nemotron-3.5-super-vl. This makes side-by-side evals possible without maintaining two provider integrations.

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