A large LLM created by combining two fine-tuned Llama 70B models into one 120B model. Combines Xwin and Euryale. Credits to - [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge the model - [mergek…
Model details →Goliath 120B vs Magnum v4 72B
Magnum v4 72B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus). The model is fine-tu…
Model details →Side-by-side comparison
| Capability | Goliath 120B | Magnum v4 72B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 6K | 16K | 🏆 Magnum v4 72B |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $3.75 | $3.00 | 🏆 Magnum v4 72B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $7.50 | $5.00 | 🏆 Magnum v4 72B |
| Tool / function calling First-class support for emitting structured tool calls. | — | — | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is Goliath 120B better than Magnum v4 72B?
Magnum v4 72B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Goliath 120B and Magnum v4 72B?
Input: $3.75 vs $3.00 per 1M tokens. Output: $7.50 vs $5.00 per 1M tokens.
What context windows do Goliath 120B and Magnum v4 72B support?
Goliath 120B supports up to 6K tokens. Magnum v4 72B supports up to 16K tokens.
Do both Goliath 120B and Magnum v4 72B support tool calling?
Goliath 120B: not advertised. Magnum v4 72B: not advertised.