OpenAI compatible API · Attested · Public status

DeepSeek: DeepSeek V3.2 vs Meta: Llama 3.1 70B Instruct

Compare DeepSeek: DeepSeek V3.2 and Meta: Llama 3.1 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

DeepSeek: DeepSeek V3.2 has the lower cheapest prompt+completion route on TrustedRouter. DeepSeek: DeepSeek V3.2 has more provider fallback routes, while DeepSeek: DeepSeek V3.2 has the larger context window. Probe-backed speed data is shown when enough recent samples exist.

$0.672/1MDeepSeek: DeepSeek V3.2 cheapest route

$0.84/1MMeta: Llama 3.1 70B Instruct cheapest route

not enough dataDeepSeek: DeepSeek V3.2 measured p50 TTFT

not enough dataMeta: Llama 3.1 70B Instruct measured p50 TTFT

DeepSeek: DeepSeek V3.2Meta: Llama 3.1 70B Instruct

Model iddeepseek/deepseek-v3.2meta-llama/llama-3.1-70b-instruct

PublisherDeepSeekCerebras

AI IQ IQ 103#56 —

Context163,840 tokens131,072 tokens

Provider routes154

Cheapest route$0.672/1M$0.84/1M

Privacy posturehas confidential-compute routeprovider posture varies

Modes chat chat

DeepSeek: DeepSeek V3.2 routes

Overview15 endpoints
PricingPrompt and completion rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Meta: Llama 3.1 70B Instruct routes

Overview4 endpoints
PricingPrompt and completion rates
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-v3.2",
    messages=messages,
)