Side-by-side comparison
Llama 3.1 70B Instruct vs Qwen3 Coder Next
Meta
Llama 3.1 70B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.4000
Output / 1M
$0.4000
Qwen
Qwen3 Coder Next
🔧 Tools
{} JSON
Input / 1M
$0.1100
Output / 1M
$0.8000
| Llama 3.1 70B Instruct | Qwen3 Coder Next | |
|---|---|---|
| Provider | Meta | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 262,144 |
| 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 → | 0.4000 | 0.1100 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4000 | 0.8000 |
Frequently asked questions
Which is cheaper, Llama 3.1 70B Instruct or Qwen3 Coder Next?
Llama 3.1 70B Instruct is cheaper than Qwen3 Coder Next on a 50/50 input/output blend by about $0.055 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 70B Instruct or Qwen3 Coder Next?
Qwen3 Coder Next has the larger context window at 262k tokens versus 131k tokens for Llama 3.1 70B Instruct. That means Qwen3 Coder Next can ingest about 2.0x as much text per request.
What is the difference between Llama 3.1 70B Instruct and Qwen3 Coder Next?
Llama 3.1 70B Instruct comes from Meta; Qwen3 Coder Next 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.