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Meta: Llama 3.3 70B Instruct vs Qwen: Qwen3.5 397B A17B

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.3 70B Instruct and Qwen3.5 397B A17B. Switch by changing the model name.

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

Monthly evidence

Meta: Llama 3.3 70B Instruct has the lower published input-plus-output rate. Qwen: Qwen3.5 397B A17B has more Credits provider routes and the larger context window. There is not enough recent probe data to compare speed.

$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route

$3.63975/1MQwen: Qwen3.5 397B A17B cheapest route

not enough dataMeta: Llama 3.3 70B Instruct fastest measured p50 TTFT

not enough dataQwen: Qwen3.5 397B A17B fastest measured p50 TTFT

The price comparison adds each route's rate for one million input tokens and one million output tokens; your cost depends on your input/output mix. Prices and live route measurements can change. Use the monthly reports when you need a stable evidence window, then run a small task-specific eval before choosing a production default.

Meta: Llama 3.3 70B InstructQwen: Qwen3.5 397B A17B

Model idmeta-llama/llama-3.3-70b-instructqwen/qwen3.5-397b-a17b

Publisher Meta Alibaba Cloud Model Studio

AI IQ — —

Context131,072 tokens262,144 tokens

Credits provider routes1011

Cheapest route$0.564425/1M$3.63975/1M

Cached input$0.1055/1M to $0.633/1M$0.047475/1M to $0.58025/1M

Privacy posturehas Confidential route (E2EE + ZDR)has Confidential route (E2EE + ZDR)

Fastest measured p50 TTFTnot enough datanot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime rangenot enough datanot enough data

Modes chat decide chat

Meta: Llama 3.3 70B Instruct routes

Overview10 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Qwen: Qwen3.5 397B A17B routes

Overview11 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Related comparisons

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Qwen: Qwen3.5 397B A17B vs Z.ai: GLM 5.344 combined provider routes
Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.343 combined provider routes
Qwen: Qwen3.5 397B A17B vs Z.ai: GLM 5.243 combined provider routes
Qwen: Qwen3.5 397B A17B vs Z.ai: GLM 5.3 Flash43 combined provider routes
Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.242 combined provider routes
Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.3 Flash42 combined provider routes
MoonshotAI: Kimi K3 vs Qwen: Qwen3.5 397B A17B39 combined provider routes
Meta: Llama 3.3 70B Instruct vs MoonshotAI: Kimi K338 combined provider routes

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-azure.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

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

Questions

Which should I use, Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.5 397B A17B?

Is Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.5 397B A17B cheaper?

The current cheapest TrustedRouter route is $0.564425/1M for Meta: Llama 3.3 70B Instruct and $3.63975/1M for Qwen: Qwen3.5 397B A17B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.5 397B A17B faster?

Current measured p50 time to first token is not enough data for Meta: Llama 3.3 70B Instruct and not enough data for Qwen: Qwen3.5 397B A17B. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Meta: Llama 3.3 70B Instruct and Qwen: Qwen3.5 397B A17B with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/llama-3.3-70b-instruct and qwen/qwen3.5-397b-a17b. This makes side-by-side evals possible without maintaining two provider integrations.