Side-by-side comparison
Llama 3.1 8B Instruct vs gpt-oss-20b
Meta
Llama 3.1 8B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.0200
Output / 1M
$0.0500
| Llama 3.1 8B Instruct | gpt-oss-20b | |
|---|---|---|
| Provider | Meta | OpenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 16,384 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0200 | 0.0300 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.0500 | 0.1400 |
Frequently asked questions
Which is cheaper, Llama 3.1 8B Instruct or gpt-oss-20b?
Llama 3.1 8B Instruct is cheaper than gpt-oss-20b 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, Llama 3.1 8B Instruct or gpt-oss-20b?
gpt-oss-20b has the larger context window at 131k tokens versus 16k tokens for Llama 3.1 8B Instruct. That means gpt-oss-20b can ingest about 8.0x as much text per request.
What is the difference between Llama 3.1 8B Instruct and gpt-oss-20b?
Llama 3.1 8B Instruct comes from Meta; gpt-oss-20b comes from OpenAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.