Side-by-side comparison
DeepSeek V4 Flash vs Llama 3.3 70B Instruct
DeepSeek
DeepSeek V4 Flash
🔧 Tools
{} JSON
Input / 1M
$0.1260
Output / 1M
$0.2520
Meta
Llama 3.3 70B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.1000
Output / 1M
$0.3200
| DeepSeek V4 Flash | Llama 3.3 70B Instruct | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 1,048,576 | 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 → | 0.1260 | 0.1000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.2520 | 0.3200 |
Frequently asked questions
Which is cheaper, DeepSeek V4 Flash or Llama 3.3 70B Instruct?
DeepSeek V4 Flash is cheaper than Llama 3.3 70B Instruct on a 50/50 input/output blend by about $0.021 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, DeepSeek V4 Flash or Llama 3.3 70B Instruct?
DeepSeek V4 Flash has the larger context window at 1M tokens versus 131k tokens for Llama 3.3 70B Instruct. That means DeepSeek V4 Flash can ingest about 8.0x as much text per request.
What is the difference between DeepSeek V4 Flash and Llama 3.3 70B Instruct?
DeepSeek V4 Flash comes from DeepSeek; Llama 3.3 70B 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.