Side-by-side comparison
Llama 3.3 Euryale 70B vs ReMM SLERP 13B
Sao10K
Llama 3.3 Euryale 70B
{} JSON
Input / 1M
$0.6500
Output / 1M
$0.7500
| Llama 3.3 Euryale 70B | ReMM SLERP 13B | |
|---|---|---|
| Provider | Sao10K | Undi95 |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 6,144 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | json_mode | json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.6500 | 0.4500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.7500 | 0.6500 |
Frequently asked questions
Which is cheaper, Llama 3.3 Euryale 70B or ReMM SLERP 13B?
ReMM SLERP 13B is cheaper than Llama 3.3 Euryale 70B on a 50/50 input/output blend by about $0.15 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 3.3 Euryale 70B or ReMM SLERP 13B?
Llama 3.3 Euryale 70B has the larger context window at 131k tokens versus 6k tokens for ReMM SLERP 13B. That means Llama 3.3 Euryale 70B can ingest about 21.3x as much text per request.
What is the difference between Llama 3.3 Euryale 70B and ReMM SLERP 13B?
Llama 3.3 Euryale 70B comes from Sao10K; ReMM SLERP 13B comes from Undi95. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.