Side-by-side comparison
Llama 3.1 8B Instruct vs Qwen3 14B
Meta
Llama 3.1 8B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.0200
Output / 1M
$0.0500
| Llama 3.1 8B Instruct | Qwen3 14B | |
|---|---|---|
| Provider | Meta | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 16,384 | 40,960 |
| 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 | 0.1000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.0500 | 0.2400 |
Frequently asked questions
Which is cheaper, Llama 3.1 8B Instruct or Qwen3 14B?
Llama 3.1 8B Instruct is cheaper than Qwen3 14B on a 50/50 input/output blend by about $0.135 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 Qwen3 14B?
Qwen3 14B has the larger context window at 41k tokens versus 16k tokens for Llama 3.1 8B Instruct. That means Qwen3 14B can ingest about 2.5x as much text per request.
What is the difference between Llama 3.1 8B Instruct and Qwen3 14B?
Llama 3.1 8B Instruct comes from Meta; Qwen3 14B comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.