Side-by-side comparison
Gemma 3n 4B vs Llama 3 8B Instruct
| Gemma 3n 4B | Llama 3 8B Instruct | |
|---|---|---|
| Provider | Meta | |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 32,768 | 8,192 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | text-only | text-only |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0600 | 0.0400 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1200 | 0.0400 |
Frequently asked questions
Which is cheaper, Gemma 3n 4B or Llama 3 8B Instruct?
Llama 3 8B Instruct is cheaper than Gemma 3n 4B on a 50/50 input/output blend by about $0.05 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Gemma 3n 4B or Llama 3 8B Instruct?
Gemma 3n 4B has the larger context window at 33k tokens versus 8k tokens for Llama 3 8B Instruct. That means Gemma 3n 4B can ingest about 4.0x as much text per request.
What is the difference between Gemma 3n 4B and Llama 3 8B Instruct?
Gemma 3n 4B comes from Google; Llama 3 8B Instruct comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.