Models
Comparison
Llama 3.1 70B vs GPT-OSS 120B
Llama 3.1 70B and GPT-OSS 120B side by side on Silicon Network: context length, capabilities, parameters, and the per-token price of each.
| Llama 3.1 70B | GPT-OSS 120B | |
|---|---|---|
| API model id | llama-3.1-70b | gpt-oss-120b |
| Base model | Llama 3.1 70B | GPT-OSS 120B |
| Family | Llama | OpenAI OSS |
| Parameters | 70B | 120B |
| Size class | Large (40B to 200B) | Large (40B to 200B) |
| Context length | 131,072 tokens (128K) | 131,072 tokens (128K) |
| Capabilities | Text | Text and Reasoning |
| Served weights | 4-bit | MXFP4-Q8 |
| Weights size | 40.7 GB | 70.7 GB |
| Input price | Unavailable | Unavailable |
| Output price | Unavailable | Unavailable |
The published rates could not be loaded just now. The pricing page reads them live.
Differences
- Both have a context window of 131,072 tokens.
- GPT-OSS 120B is the larger model by total parameters: 120B against 70B.
- Reasoning: GPT-OSS 120B only.
Whether a model is loaded on a node right now changes through the day; the pricing page shows it live. A model that is not loaded answers 404 until an operator loads it.
About these figures
Context length, capabilities, and weights size come from the model card each id is served with. Rates are the published per-token prices, refreshed every few minutes. There are no speed figures here: the network does not publish per-model throughput yet.
Silicon Network›Models›Llama 3.1 70B vs GPT-OSS 120B13 items