Auto-generated comparison

Google: Gemma 2 27B vs Meta: Llama 3.1 405B Instruct

Google: Gemma 2 27B and Meta: Llama 3.1 405B Instruct are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.

Side-by-side comparison

CapabilityGoogle: Gemma 2 27BMeta: Llama 3.1 405B InstructWinner
Context window
Maximum number of input tokens the model can attend to in a single request.
8K131K🏆 Meta: Llama 3.1 405B Instruct
Input price (per 1M)
Cost per million input tokens billed by the provider.
$0.65$4.00🏆 Google: Gemma 2 27B
Output price (per 1M)
Cost per million output tokens billed by the provider.
$0.65$4.00🏆 Google: Gemma 2 27B
Tool / function calling
First-class support for emitting structured tool calls.
Yes🏆 Meta: Llama 3.1 405B Instruct
Vision input
Accepts image inputs alongside text.
Tie
Reasoning mode
Internal chain-of-thought / extended-thinking support.
Tie

Frequently asked questions

Is Google: Gemma 2 27B better than Meta: Llama 3.1 405B Instruct?

Google: Gemma 2 27B and Meta: Llama 3.1 405B Instruct are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.

What's the price difference between Google: Gemma 2 27B and Meta: Llama 3.1 405B Instruct?

Input: $0.65 vs $4.00 per 1M tokens. Output: $0.65 vs $4.00 per 1M tokens.

What context windows do Google: Gemma 2 27B and Meta: Llama 3.1 405B Instruct support?

Google: Gemma 2 27B supports up to 8K tokens. Meta: Llama 3.1 405B Instruct supports up to 131K tokens.

Do both Google: Gemma 2 27B and Meta: Llama 3.1 405B Instruct support tool calling?

Google: Gemma 2 27B: not advertised. Meta: Llama 3.1 405B Instruct: yes.

Compare Google: Gemma 2 27B with other models

Compare Meta: Llama 3.1 405B Instruct with other models