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DeepSeek: R1 0528 vs Meta: Llama 3.1 8B Instruct

Try both on us. Starter credit covers your first requests, then one key routes R1 0528 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

R1 0528 has the larger context window. Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token.

$2.79575/1MDeepSeek: R1 0528 cheapest route

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

1672 msDeepSeek: R1 0528 fastest measured p50 TTFT via io-net

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

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: R1 0528Meta: Llama 3.1 8B Instruct

Model iddeepseek/deepseek-r1-0528meta-llama/llama-3.1-8b-instruct

Publisher DeepSeek Meta

AI IQ — —

Context163,840 tokens131,072 tokens

Credits provider routes35

Cheapest route$2.79575/1M$0.07385/1M

Cached input$0.276235/1M to $0.36925/1M$0.211/1M

Privacy postureprovider posture varieshas ZDR route

Fastest measured p50 TTFT1672 ms via io-net1180 ms via wandb

Highest measured throughputnot enough datanot enough data

Recent route uptime range100.00%0.00% to 100.00%

Modes chat chat

DeepSeek: R1 0528 routes

Overview3 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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DeepSeek: R1 0528 vs Z.ai: GLM 5.336 combined provider routes
DeepSeek: R1 0528 vs Z.ai: GLM 5.235 combined provider routes
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Meta: Llama 3.1 8B Instruct vs MoonshotAI: Kimi K333 combined provider routes
DeepSeek: R1 0528 vs MoonshotAI: Kimi K331 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="deepseek/deepseek-r1-0528",
    messages=messages,
)

Questions

Which should I use, DeepSeek: R1 0528 or Meta: Llama 3.1 8B Instruct?

R1 0528 has the larger context window. Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token.

Is DeepSeek: R1 0528 or Meta: Llama 3.1 8B Instruct cheaper?

The current cheapest TrustedRouter route is $2.79575/1M for DeepSeek: R1 0528 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: R1 0528 or Meta: Llama 3.1 8B Instruct faster?

Current measured p50 time to first token is 1672 ms for DeepSeek: R1 0528 and 1180 ms 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: R1 0528 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-r1-0528 and meta-llama/llama-3.1-8b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.