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Meta: Llama 3.3 70B Instruct vs Qwen: Qwen3.8 2.4T A95B

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.3 70B Instruct and Qwen3.8 2.4T A95B. 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, more Credits provider routes and the lower measured p50 time to first token. Qwen: Qwen3.8 2.4T A95B has the larger context window.

$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route
$5.275/1MQwen: Qwen3.8 2.4T A95B cheapest route
1186 msMeta: Llama 3.3 70B Instruct fastest measured p50 TTFT via scaleway
1535 msQwen: Qwen3.8 2.4T A95B fastest measured p50 TTFT via lyceum

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: Qwen3.8 2.4T A95B
Model idmeta-llama/llama-3.3-70b-instructqwen/qwen3.8-2.4t-a95b
AI IQ — IQ 123#32
Context131,072 tokens1,000,000 tokens
Credits provider routes106
Cheapest route$0.564425/1M$5.275/1M
Cached input$0.1055/1M to $0.633/1M$0.26375/1M to $0.66465/1M
Privacy posturehas Confidential route (E2EE + ZDR)has ZDR route
Fastest measured p50 TTFT1186 ms via scaleway1535 ms via lyceum
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%100.00%
Modes chat decide chat

Meta: Llama 3.3 70B Instruct routes

Qwen: Qwen3.8 2.4T A95B routes

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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,
)

Questions

Which should I use, Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.8 2.4T A95B?

Meta: Llama 3.3 70B Instruct has the lower published input-plus-output rate, more Credits provider routes and the lower measured p50 time to first token. Qwen: Qwen3.8 2.4T A95B has the larger context window.

Is Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.8 2.4T A95B cheaper?

The current cheapest TrustedRouter route is $0.564425/1M for Meta: Llama 3.3 70B Instruct and $5.275/1M for Qwen: Qwen3.8 2.4T A95B. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.3 70B Instruct or Qwen: Qwen3.8 2.4T A95B faster?

Current measured p50 time to first token is 1186 ms for Meta: Llama 3.3 70B Instruct and 1535 ms for Qwen: Qwen3.8 2.4T A95B. 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: Qwen3.8 2.4T A95B 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/qwen3.8-2.4t-a95b. This makes side-by-side evals possible without maintaining two provider integrations.

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