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deepseek-ai/DeepSeek-V3.1 vs Meta: Llama 3.3 70B Instruct

Try both on us. Starter credit covers your first requests, then one key routes deepseek-ai/DeepSeek-V3.1 and Llama 3.3 70B 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-ai/DeepSeek-V3.1 has the larger context window. Meta: Llama 3.3 70B Instruct has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

$1.266/1Mdeepseek-ai/DeepSeek-V3.1 cheapest route

$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route

not enough datadeepseek-ai/DeepSeek-V3.1 fastest measured p50 TTFT

not enough dataMeta: Llama 3.3 70B 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-ai/DeepSeek-V3.1Meta: Llama 3.3 70B Instruct

Model iddeepseek/deepseek-v3.1meta-llama/llama-3.3-70b-instruct

Publisher DeepSeek Meta

AI IQ IQ 98#131 —

Context163,840 tokens131,072 tokens

Credits provider routes410

Cheapest route$1.266/1M$0.564425/1M

Cached input$0.13715/1M to $0.241595/1M$0.1055/1M to $0.633/1M

Privacy postureprovider posture varieshas Confidential route (E2EE + ZDR)

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 decide

deepseek-ai/DeepSeek-V3.1 routes

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

Meta: Llama 3.3 70B Instruct routes

Overview10 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
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-v3.1",
    messages=messages,
)

Questions

Which should I use, deepseek-ai/DeepSeek-V3.1 or Meta: Llama 3.3 70B Instruct?

Is deepseek-ai/DeepSeek-V3.1 or Meta: Llama 3.3 70B Instruct cheaper?

The current cheapest TrustedRouter route is $1.266/1M for deepseek-ai/DeepSeek-V3.1 and $0.564425/1M for Meta: Llama 3.3 70B Instruct. The comparison uses current catalog prices and updates as provider pricing changes.

Is deepseek-ai/DeepSeek-V3.1 or Meta: Llama 3.3 70B Instruct faster?

Current measured p50 time to first token is not enough data for deepseek-ai/DeepSeek-V3.1 and not enough data for Meta: Llama 3.3 70B Instruct. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test deepseek-ai/DeepSeek-V3.1 and Meta: Llama 3.3 70B 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-v3.1 and meta-llama/llama-3.3-70b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.