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Llama 3.3 70B Instruct vs Ministral 3 8B

meta-llama/llama-3.3-70b-instruct · mistralai/ministral-3-8b-instruct

As of October 31, 2026, Ministral 3 8B is the cheaper API on UberLLM: $0.0018 per million input tokens and $0.0018 per million output, versus $0.0479 / $0.1533 for Llama 3.3 70B Instruct, about 99% less when output is 3 tokens for every input token. These are the median prices buyers paid over the last 24 hours. Both work with one OpenAI-compatible key and UberLLM adds no fee. Choose Ministral 3 8B to cut cost; choose Llama 3.3 70B Instruct when its capabilities fit your task better.

Llama 3.3 70B Instruct vs Ministral 3 8B, side by side

SpecLlama 3.3 70B InstructMinistral 3 8B
Price · input / 1M$0.0479$0.0018
Price · output / 1M$0.1533$0.0018
Context length128,000128,000
Max output tokens4,0968,000
Input modalitiestexttext, image
Output modalitiestexttext
Tools / functionsYesYes
Vision (image input)—Yes
% off list52% off99% off

Median prices buyers paid on UberLLM over the last 24 hours. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated October 31, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?

Llama 3.3 70B Instruct vs Ministral 3 8B — FAQ

Is Llama 3.3 70B Instruct or Ministral 3 8B cheaper?

Ministral 3 8B is cheaper on a blended token mix, by about 99%. A request costs what its provider charged, UberLLM adds no fee, and every request is listed with its cost in Activity.

What's the price difference between Llama 3.3 70B Instruct and Ministral 3 8B?

Llama 3.3 70B Instruct: $0.0479 in / $0.1533 out per 1M tokens. Ministral 3 8B: $0.0018 in / $0.0018 out per 1M tokens. That's roughly a 99% blended difference. Prices are live; UberLLM adds no fee.

Can I use both Llama 3.3 70B Instruct and Ministral 3 8B with one API?

Yes. Both are served through a single OpenAI-compatible endpoint — set the base URL to https://api.uberllm.dev/v1 and your UberLLM key, then switch between them by changing the model id. Anthropic SDKs work via https://api.uberllm.dev/v1/messages.

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