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Meta: Llama 3.1 8B Instruct vs Thinking Machines: Inkling

Try both on us. Starter credit covers your first requests, then one key routes Llama 3.1 8B Instruct and Inkling. 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, more Credits provider routes and the lower measured p50 time to first token. Thinking Machines: Inkling has the larger context window.

$0.07385/1MMeta: Llama 3.1 8B Instruct cheapest route

$5.32775/1MThinking Machines: Inkling cheapest route

1180 msMeta: Llama 3.1 8B Instruct fastest measured p50 TTFT via wandb

1441 msThinking Machines: Inkling fastest measured p50 TTFT via thinkingmachines

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 InstructThinking Machines: Inkling

Model idmeta-llama/llama-3.1-8b-instructthinkingmachines/inkling

Publisher Meta Thinking Machines Lab

AI IQ — IQ 107#88

Context131,072 tokens524,288 tokens

Credits provider routes53

Cheapest route$0.07385/1M$5.32775/1M

Cached input$0.211/1M$0.17935/1M

Privacy posturehas ZDR routehas ZDR route

Fastest measured p50 TTFT1180 ms via wandb1441 ms via thinkingmachines

Highest measured throughputnot enough datanot enough data

Recent route uptime range0.00% to 100.00%100.00%

Modes chat chat

Meta: Llama 3.1 8B Instruct routes

Overview5 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Thinking Machines: Inkling routes

Overview3 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

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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 Thinking Machines: Inkling?

Is Meta: Llama 3.1 8B Instruct or Thinking Machines: Inkling cheaper?

The current cheapest TrustedRouter route is $0.07385/1M for Meta: Llama 3.1 8B Instruct and $5.32775/1M for Thinking Machines: Inkling. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.1 8B Instruct or Thinking Machines: Inkling faster?

Current measured p50 time to first token is 1180 ms for Meta: Llama 3.1 8B Instruct and 1441 ms for Thinking Machines: Inkling. 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 Thinking Machines: Inkling 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 thinkingmachines/inkling. This makes side-by-side evals possible without maintaining two provider integrations.