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Meta: Llama 3.1 8B Instruct vs nvidia/Nemotron-3.5-Lightning-30B-A3B

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.1 8B Instruct and nvidia/Nemotron-3.5-Lightning-30B-A3B. 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

Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate and more Credits provider routes. nvidia/Nemotron-3.5-Lightning-30B-A3B has the larger context window and the lower measured p50 time to first token.

$0.07385/1MMeta: Llama 3.1 8B Instruct cheapest route
$0.26375/1Mnvidia/Nemotron-3.5-Lightning-30B-A3B cheapest route
1319 msMeta: Llama 3.1 8B Instruct fastest measured p50 TTFT via wandb
812 msnvidia/Nemotron-3.5-Lightning-30B-A3B fastest measured p50 TTFT via nvidia-nim

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.

Meta: Llama 3.1 8B Instructnvidia/Nemotron-3.5-Lightning-30B-A3B
Model idmeta-llama/llama-3.1-8b-instructnvidia/nemotron-3.5-lightning-30b-a3b
Publisher Meta NVIDIA
AI IQ — —
Context131,072 tokens262,144 tokens
Credits provider routes53
Cheapest route$0.07385/1M$0.26375/1M
Cached input$0.211/1M$0.03165/1M to $0.0422/1M
Privacy posturehas ZDR routeprovider posture varies
Fastest measured p50 TTFT1319 ms via wandb812 ms via nvidia-nim
Highest measured throughputnot enough datanot enough data
Recent route uptime range0.00% to 100.00%100.00%
Modes chat chat

Meta: Llama 3.1 8B Instruct routes

nvidia/Nemotron-3.5-Lightning-30B-A3B 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="meta-llama/llama-3.1-8b-instruct",
    messages=messages,
)

Questions

Which should I use, Meta: Llama 3.1 8B Instruct or nvidia/Nemotron-3.5-Lightning-30B-A3B?

Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate and more Credits provider routes. nvidia/Nemotron-3.5-Lightning-30B-A3B has the larger context window and the lower measured p50 time to first token.

Is Meta: Llama 3.1 8B Instruct or nvidia/Nemotron-3.5-Lightning-30B-A3B cheaper?

The current cheapest TrustedRouter route is $0.07385/1M for Meta: Llama 3.1 8B Instruct and $0.26375/1M for nvidia/Nemotron-3.5-Lightning-30B-A3B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.1 8B Instruct or nvidia/Nemotron-3.5-Lightning-30B-A3B faster?

Current measured p50 time to first token is 1319 ms for Meta: Llama 3.1 8B Instruct and 812 ms for nvidia/Nemotron-3.5-Lightning-30B-A3B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Meta: Llama 3.1 8B Instruct and nvidia/Nemotron-3.5-Lightning-30B-A3B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/llama-3.1-8b-instruct and nvidia/nemotron-3.5-lightning-30b-a3b. This makes side-by-side evals possible without maintaining two provider integrations.

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