OpenAI compatible API · Attested · Public status

Meta: Llama 3.1 70B Instruct vs MoonshotAI: Kimi K2.6

Compare Meta: Llama 3.1 70B Instruct and MoonshotAI: Kimi K2.6 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 3.1 70B Instruct has the lower cheapest prompt+completion route on TrustedRouter. MoonshotAI: Kimi K2.6 has more provider fallback routes, while MoonshotAI: Kimi K2.6 has the larger context window. Current TrustedRouter probes show Meta: Llama 3.1 70B Instruct with the lower p50 TTFT.

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

$4.158/1MMoonshotAI: Kimi K2.6 cheapest route

891 msMeta: Llama 3.1 70B Instruct measured p50 TTFT

1555 msMoonshotAI: Kimi K2.6 measured p50 TTFT

Meta: Llama 3.1 70B InstructMoonshotAI: Kimi K2.6

Model idmeta-llama/llama-3.1-70b-instructmoonshotai/kimi-k2.6

PublisherCerebrasKimi

AI IQ — IQ 119#19

Context131,072 tokens262,144 tokens

Provider routes432

Cheapest route$0.84/1M$4.158/1M

Privacy postureprovider posture varieshas provider E2EE route

Modes chat chat

Meta: Llama 3.1 70B Instruct routes

Overview4 endpoints
PricingPrompt and completion rates
ProvidersAll serving providers

MoonshotAI: Kimi K2.6 routes

Overview32 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://api.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.1-70b-instruct",
    messages=messages,
)