OpenAI compatible API · Attested · Public status
Meta: Llama 3.3 70B Instruct vs DeepSeek: DeepSeek V4 Flash
Compare Meta: Llama 3.3 70B Instruct and DeepSeek: DeepSeek V4 Flash by providers, context, price, and TrustedRouter route support.
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 V4 Flash has the lower cheapest prompt+completion route on TrustedRouter. DeepSeek: DeepSeek V4 Flash has more provider fallback routes, while DeepSeek: DeepSeek V4 Flash has the larger context window. Current TrustedRouter probes show DeepSeek: DeepSeek V4 Flash with the lower p50 TTFT.
$0.526575/1MMeta: Llama 3.3 70B Instruct cheapest route
$0.2835/1MDeepSeek: DeepSeek V4 Flash cheapest route
2397 msMeta: Llama 3.3 70B Instruct measured p50 TTFT
2022 msDeepSeek: DeepSeek V4 Flash measured p50 TTFT
Meta: Llama 3.3 70B InstructDeepSeek: DeepSeek V4 Flash
Model id
meta-llama/llama-3.3-70b-instructdeepseek/deepseek-v4-flash
PublisherCerebrasDeepSeek
Context131,072 tokens1,048,576 tokens
Provider routes1419
Cheapest route$0.526575/1M$0.2835/1M
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
DeepSeek: DeepSeek V4 Flash routes
- Overview19 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-3.3-70b-instruct",
messages=messages,
)