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DeepSeek V4 Pro 0423 vs Meta: Llama 3.1 8B Instruct

Try both on us. Starter credit covers your first requests, then one key routes DeepSeek V4 Pro 0423 and Llama 3.1 8B Instruct. 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 the larger context window. Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

$4.1145/1MDeepSeek V4 Pro 0423 cheapest route

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

not enough dataDeepSeek V4 Pro 0423 fastest measured p50 TTFT

not enough dataMeta: Llama 3.1 8B Instruct fastest measured p50 TTFT

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 V4 Pro 0423Meta: Llama 3.1 8B Instruct

Model iddeepseek/deepseek-v4-pro-0423meta-llama/llama-3.1-8b-instruct

Publisher DeepSeek Meta

AI IQ — —

Context1,048,576 tokens131,072 tokens

Credits provider routes45

Cheapest route$4.1145/1M$0.07385/1M

Cached input$0.1055/1M to $0.34815/1M$0.211/1M

Privacy posturehas ZDR routehas ZDR route

Fastest measured p50 TTFTnot enough datanot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime rangenot enough datanot enough data

Modes chat chat

DeepSeek V4 Pro 0423 routes

Overview4 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Meta: Llama 3.1 8B Instruct routes

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

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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-azure.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro-0423",
    messages=messages,
)

Questions

Which should I use, DeepSeek V4 Pro 0423 or Meta: Llama 3.1 8B Instruct?

Is DeepSeek V4 Pro 0423 or Meta: Llama 3.1 8B Instruct cheaper?

The current cheapest TrustedRouter route is $4.1145/1M for DeepSeek V4 Pro 0423 and $0.07385/1M for Meta: Llama 3.1 8B Instruct. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek V4 Pro 0423 or Meta: Llama 3.1 8B Instruct faster?

Current measured p50 time to first token is not enough data for DeepSeek V4 Pro 0423 and not enough data for Meta: Llama 3.1 8B Instruct. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test DeepSeek V4 Pro 0423 and Meta: Llama 3.1 8B Instruct 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-0423 and meta-llama/llama-3.1-8b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.