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Meta: Llama 3.1 8B Instruct vs Qwen: Qwen3.8 2.4T A95B

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.1 8B 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 3.1 8B Instruct has the lower published input-plus-output rate and the lower measured p50 time to first token. Qwen: Qwen3.8 2.4T A95B has more Credits provider routes and the larger context window.

$0.07385/1MMeta: Llama 3.1 8B Instruct cheapest route
$5.275/1MQwen: Qwen3.8 2.4T A95B cheapest route
865 msMeta: Llama 3.1 8B Instruct fastest measured p50 TTFT via telnyx
1103 msQwen: Qwen3.8 2.4T A95B fastest measured p50 TTFT via together

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 3.1 8B InstructQwen: Qwen3.8 2.4T A95B
Model idmeta-llama/llama-3.1-8b-instructqwen/qwen3.8-2.4t-a95b
AI IQ — IQ 123#36
Context131,072 tokens1,000,000 tokens
Credits provider routes56
Cheapest route$0.07385/1M$5.275/1M
Cached input$0.211/1M$0.26375/1M to $0.66465/1M
Privacy posturehas ZDR routehas ZDR route
Fastest measured p50 TTFT865 ms via telnyx1103 ms via together
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%100.00%
Modes chat chat

Meta: Llama 3.1 8B 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-3.1-8b-instruct",
    messages=messages,
)

Questions

Which should I use, Meta: Llama 3.1 8B Instruct or Qwen: Qwen3.8 2.4T A95B?

Meta: Llama 3.1 8B Instruct has the lower published input-plus-output rate and the lower measured p50 time to first token. Qwen: Qwen3.8 2.4T A95B has more Credits provider routes and the larger context window.

Is Meta: Llama 3.1 8B Instruct or Qwen: Qwen3.8 2.4T A95B cheaper?

The current cheapest TrustedRouter route is $0.07385/1M for Meta: Llama 3.1 8B 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 3.1 8B Instruct or Qwen: Qwen3.8 2.4T A95B faster?

Current measured p50 time to first token is 865 ms for Meta: Llama 3.1 8B Instruct and 1103 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 3.1 8B 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-3.1-8b-instruct and qwen/qwen3.8-2.4t-a95b. This makes side-by-side evals possible without maintaining two provider integrations.

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