Auto-generated comparison

Meta: Llama 3.1 405B (base) vs Mistral: Mixtral 8x22B Instruct

Mistral: Mixtral 8x22B Instruct wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.

Side-by-side comparison

CapabilityMeta: Llama 3.1 405B (base)Mistral: Mixtral 8x22B InstructWinner
Context window
Maximum number of input tokens the model can attend to in a single request.
33K66K🏆 Mistral: Mixtral 8x22B Instruct
Input price (per 1M)
Cost per million input tokens billed by the provider.
$4.00$2.00🏆 Mistral: Mixtral 8x22B Instruct
Output price (per 1M)
Cost per million output tokens billed by the provider.
$4.00$6.00🏆 Meta: Llama 3.1 405B (base)
Tool / function calling
First-class support for emitting structured tool calls.
Yes🏆 Mistral: Mixtral 8x22B Instruct
Vision input
Accepts image inputs alongside text.
Tie
Reasoning mode
Internal chain-of-thought / extended-thinking support.
Tie

Frequently asked questions

Is Meta: Llama 3.1 405B (base) better than Mistral: Mixtral 8x22B Instruct?

Mistral: Mixtral 8x22B Instruct wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.

What's the price difference between Meta: Llama 3.1 405B (base) and Mistral: Mixtral 8x22B Instruct?

Input: $4.00 vs $2.00 per 1M tokens. Output: $4.00 vs $6.00 per 1M tokens.

What context windows do Meta: Llama 3.1 405B (base) and Mistral: Mixtral 8x22B Instruct support?

Meta: Llama 3.1 405B (base) supports up to 33K tokens. Mistral: Mixtral 8x22B Instruct supports up to 66K tokens.

Do both Meta: Llama 3.1 405B (base) and Mistral: Mixtral 8x22B Instruct support tool calling?

Meta: Llama 3.1 405B (base): not advertised. Mistral: Mixtral 8x22B Instruct: yes.

Compare Meta: Llama 3.1 405B (base) with other models

Compare Mistral: Mixtral 8x22B Instruct with other models