OpenAI compatible API · Attested · Public status

DeepSeek: R1 0528 vs Meta: Llama 3.3 70B Instruct

Compare DeepSeek: R1 0528 and Meta: Llama 3.3 70B Instruct by providers, context, price, and TrustedRouter route support.

Verify gateway

Onebase URL to migrate

100sof models and routes

0prompt or output logs. Always.

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

Meta: Llama 3.3 70B Instruct has the lower cheapest prompt+completion route on TrustedRouter. Meta: Llama 3.3 70B Instruct has more provider fallback routes, while DeepSeek: R1 0528 has the larger context window. Probe-backed speed data is shown when enough recent samples exist.

$2.7825/1MDeepSeek: R1 0528 cheapest route

$0.56175/1MMeta: Llama 3.3 70B Instruct cheapest route

not enough dataDeepSeek: R1 0528 measured p50 TTFT

not enough dataMeta: Llama 3.3 70B Instruct measured p50 TTFT

DeepSeek: R1 0528Meta: Llama 3.3 70B Instruct

Model iddeepseek/deepseek-r1-0528meta-llama/llama-3.3-70b-instruct

PublisherDeepSeekCerebras

AI IQ — —

Context163,840 tokens131,072 tokens

Provider routes514

Cheapest route$2.7825/1M$0.56175/1M

Privacy postureprovider posture varieshas provider E2EE route

Modes chat chat

DeepSeek: R1 0528 routes

Overview5 endpoints
PricingPrompt and completion rates
ProvidersAll serving providers

Meta: Llama 3.3 70B Instruct routes

Overview14 endpoints
PricingPrompt and completion rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

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://gchircrcif.eu-west-3.awsapprunner.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="deepseek/deepseek-r1-0528",
    messages=messages,
)