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Meta: Llama 3.1 8B Instruct vs NVIDIA: Nemotron 3.5 Lightning

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.1 8B Instruct and Nemotron 3.5 Lightning. 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 has the larger context window and the lower measured p50 time to first token.

$0.07385/1MMeta: Llama 3.1 8B Instruct cheapest route

$0.223309/1MNVIDIA: Nemotron 3.5 Lightning cheapest route

1180 msMeta: Llama 3.1 8B Instruct fastest measured p50 TTFT via wandb

841 msNVIDIA: Nemotron 3.5 Lightning 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.

Meta: Llama 3.1 8B InstructNVIDIA: Nemotron 3.5 Lightning

Model idmeta-llama/llama-3.1-8b-instructnvidia/nemotron-3.5-lightning

Publisher Meta NVIDIA

AI IQ — —

Context131,072 tokens262,144 tokens

Credits provider routes53

Cheapest route$0.07385/1M$0.223309/1M

Cached input$0.211/1M$0.01055/1M to $0.03165/1M

Privacy posturehas ZDR routeprovider posture varies

Fastest measured p50 TTFT1180 ms via wandb841 ms via io-net

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

Overview5 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

NVIDIA: Nemotron 3.5 Lightning routes

Overview3 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

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NVIDIA: Nemotron 3.5 Lightning vs Z.ai: GLM 5.336 combined provider routes
NVIDIA: Nemotron 3.5 Lightning vs Z.ai: GLM 5.235 combined provider routes
NVIDIA: Nemotron 3.5 Lightning vs Z.ai: GLM 5.3 Flash35 combined provider routes
Meta: Llama 3.1 8B Instruct vs MoonshotAI: Kimi K333 combined provider routes
DeepSeek: DeepSeek V4 Flash 0731 vs Meta: Llama 3.1 8B Instruct31 combined provider routes

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?

Is Meta: Llama 3.1 8B Instruct or NVIDIA: Nemotron 3.5 Lightning cheaper?

The current cheapest TrustedRouter route is $0.07385/1M for Meta: Llama 3.1 8B Instruct and $0.223309/1M for NVIDIA: Nemotron 3.5 Lightning. 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 faster?

Current measured p50 time to first token is 1180 ms for Meta: Llama 3.1 8B Instruct and 841 ms for NVIDIA: Nemotron 3.5 Lightning. 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 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. This makes side-by-side evals possible without maintaining two provider integrations.