Side-by-side comparison
ReMM SLERP 13B vs Olmo 3 32B Think
| ReMM SLERP 13B | Olmo 3 32B Think | |
|---|---|---|
| Provider | Undi95 | AllenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 6,144 | 65,536 |
| 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 → | 0.4500 | 0.1500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.6500 | 0.5000 |
Frequently asked questions
Which is cheaper, ReMM SLERP 13B or Olmo 3 32B Think?
Olmo 3 32B Think is cheaper than ReMM SLERP 13B on a 50/50 input/output blend by about $0.225 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, ReMM SLERP 13B or Olmo 3 32B Think?
Olmo 3 32B Think has the larger context window at 66k tokens versus 6k tokens for ReMM SLERP 13B. That means Olmo 3 32B Think can ingest about 10.7x as much text per request.
What is the difference between ReMM SLERP 13B and Olmo 3 32B Think?
ReMM SLERP 13B comes from Undi95; Olmo 3 32B Think comes from AllenAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.