OpenAI compatible API · Attested · Public status

Meta: Llama 3.3 70B Instruct vs MiniMax: MiniMax M2.5

Compare Meta: Llama 3.3 70B Instruct and MiniMax: MiniMax M2.5 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 MiniMax: MiniMax M2.5 has the larger context window. Current TrustedRouter probes show Meta: Llama 3.3 70B Instruct with the lower p50 TTFT.

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

$1.1025/1MMiniMax: MiniMax M2.5 cheapest route

849 msMeta: Llama 3.3 70B Instruct measured p50 TTFT

901 msMiniMax: MiniMax M2.5 measured p50 TTFT

Meta: Llama 3.3 70B InstructMiniMax: MiniMax M2.5

Model idmeta-llama/llama-3.3-70b-instructminimax/minimax-m2.5

PublisherCerebrasFriendliAI

AI IQ — IQ 105#54

Context131,072 tokens204,800 tokens

Provider routes1414

Cheapest route$0.56175/1M$1.1025/1M

Privacy posturehas provider E2EE routehas ZDR route

Modes chat chat

Meta: Llama 3.3 70B Instruct routes

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

MiniMax: MiniMax M2.5 routes

Overview14 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://api.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.3-70b-instruct",
    messages=messages,
)