OpenAI compatible API · Attested · Public status

Meta: Llama 3.3 70B Instruct vs Qwen: Qwen3.6 35B A3B

Compare Meta: Llama 3.3 70B Instruct and Qwen: Qwen3.6 35B A3B 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 Qwen: Qwen3.6 35B A3B has the larger context window. Current TrustedRouter probes show Meta: Llama 3.3 70B Instruct with the lower p50 TTFT.

$0.526575/1MMeta: Llama 3.3 70B Instruct cheapest route

$1.043243/1MQwen: Qwen3.6 35B A3B cheapest route

2566 msMeta: Llama 3.3 70B Instruct measured p50 TTFT

2860 msQwen: Qwen3.6 35B A3B measured p50 TTFT

Meta: Llama 3.3 70B InstructQwen: Qwen3.6 35B A3B

Model idmeta-llama/llama-3.3-70b-instructqwen/qwen3.6-35b-a3b

PublisherCerebrasParasail

AI IQ — IQ 100#70

Context131,072 tokens262,144 tokens

Provider routes1412

Cheapest route$0.526575/1M$1.043243/1M

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

Qwen: Qwen3.6 35B A3B routes

Overview12 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,
)