Meta: Llama 3.3 70B Instruct vs Thinking Machines: Inkling
Try both on us. Starter credit covers your first requests, then one key routes Llama 3.3 70B Instruct and Inkling. Switch by changing the model name.
Practical read
Monthly evidenceMeta: 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. Thinking Machines: Inkling has the larger context window.
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/llama-3.3-70b-instructthinkingmachines/inkling
Meta: Llama 3.3 70B Instruct routes
- Overview10 Credits routes
- PricingInput, cached input, and output rates
- BenchmarksTrustedRouter and external sources
- ProvidersAll serving providers
Related comparisons
Browse every comparison- Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.343 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
- Meta: Llama 3.3 70B Instruct vs MoonshotAI: Kimi K338 combined provider routes
- DeepSeek: DeepSeek V4 Flash 0731 vs Meta: Llama 3.3 70B Instruct36 combined provider routes
- Thinking Machines: Inkling vs Z.ai: GLM 5.336 combined provider routes
- Thinking Machines: Inkling vs Z.ai: GLM 5.235 combined provider routes
- Thinking Machines: Inkling vs Z.ai: GLM 5.3 Flash35 combined provider routes
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.
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 Thinking Machines: Inkling?
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. Thinking Machines: Inkling has the larger context window.
Is Meta: Llama 3.3 70B Instruct or Thinking Machines: Inkling cheaper?
The current cheapest TrustedRouter route is $0.564425/1M for Meta: Llama 3.3 70B Instruct and $5.32775/1M for Thinking Machines: Inkling. The comparison uses current catalog prices and updates as provider pricing changes.
Is Meta: Llama 3.3 70B Instruct or Thinking Machines: Inkling faster?
Current measured p50 time to first token is 1186 ms for Meta: Llama 3.3 70B 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 3.3 70B 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-3.3-70b-instruct and thinkingmachines/inkling. This makes side-by-side evals possible without maintaining two provider integrations.