Auto-generated comparison

Inception: Mercury vs Meta: Llama 3.3 70B Instruct

Meta: Llama 3.3 70B Instruct wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.

Side-by-side comparison

CapabilityInception: MercuryMeta: Llama 3.3 70B InstructWinner
Context window
Maximum number of input tokens the model can attend to in a single request.
128K131K🏆 Meta: Llama 3.3 70B Instruct
Input price (per 1M)
Cost per million input tokens billed by the provider.
$0.25$0.10🏆 Meta: Llama 3.3 70B Instruct
Output price (per 1M)
Cost per million output tokens billed by the provider.
$0.75$0.32🏆 Meta: Llama 3.3 70B Instruct
Tool / function calling
First-class support for emitting structured tool calls.
YesYesTie
Vision input
Accepts image inputs alongside text.
Tie
Reasoning mode
Internal chain-of-thought / extended-thinking support.
Tie

Frequently asked questions

Is Inception: Mercury better than Meta: Llama 3.3 70B Instruct?

Meta: Llama 3.3 70B Instruct wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.

What's the price difference between Inception: Mercury and Meta: Llama 3.3 70B Instruct?

Input: $0.25 vs $0.10 per 1M tokens. Output: $0.75 vs $0.32 per 1M tokens.

What context windows do Inception: Mercury and Meta: Llama 3.3 70B Instruct support?

Inception: Mercury supports up to 128K tokens. Meta: Llama 3.3 70B Instruct supports up to 131K tokens.

Do both Inception: Mercury and Meta: Llama 3.3 70B Instruct support tool calling?

Inception: Mercury: yes. Meta: Llama 3.3 70B Instruct: yes.

Compare Inception: Mercury with other models

Compare Meta: Llama 3.3 70B Instruct with other models