OpenAI compatible API · Attested · Public status

Meta: Llama 3.3 70B Instruct vs Google: Gemma 4 26B A4B

Compare Meta: Llama 3.3 70B Instruct and Google: Gemma 4 26B A4B by providers, context, price, and TrustedRouter route support.

Verify gateway

Onebase URL to migrate

100sof models and routes

Noneprompt logs by default

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

Google: Gemma 4 26B A4B has the lower cheapest prompt+completion route on TrustedRouter. Meta: Llama 3.3 70B Instruct has more provider fallback routes, while Google: Gemma 4 26B A4B 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

$0.4305/1MGoogle: Gemma 4 26B A4B cheapest route

2217 msMeta: Llama 3.3 70B Instruct measured p50 TTFT

5080 msGoogle: Gemma 4 26B A4B measured p50 TTFT

Meta: Llama 3.3 70B InstructGoogle: Gemma 4 26B A4B

Model idmeta-llama/llama-3.3-70b-instructgoogle/gemma-4-26b-a4b-it

PublisherCerebrasGoogle AI Studio

AI IQ — IQ 97#77

Context131,072 tokens262,144 tokens

Provider routes1411

Cheapest route$0.526575/1M$0.4305/1M

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

Google: Gemma 4 26B A4B routes

Overview11 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,
)