Magnum v4 72B
Description
Magnum v4 72B is a fine-tuned version of Qwen2.5 72B that aims to replicate the prose quality of Claude 3 models, specifically Sonnet and Opus. This model is designed for creative writing and roleplay scenarios, offering high-quality text generation with a focus on narrative and conversational abilities.
The model uses the ChatML instruction format and is optimized for generating coherent, engaging prose that matches the stylistic qualities of Anthropic's Claude 3 family.
Technical Specifications
| Specification |
Value |
| Context Window |
32,768 tokens |
| Context Length |
16,384 tokens |
| Underlying Model Context |
32,768 tokens |
| Max Completion Tokens |
2,048 |
| Input Modalities |
Text |
| Output Modalities |
Text |
| Quantization |
FP8 |
Pricing
| Type |
Price |
| Input |
$3.00 per 1M tokens |
| Output |
$5.00 per 1M tokens |
- Input: $0.000003 per token
- Output: $0.000005 per token
Supported Parameters
| Parameter |
Supported |
response_format |
Yes |
max_tokens |
Yes |
temperature |
Yes |
top_p |
Yes |
stop |
Yes |
frequency_penalty |
Yes |
presence_penalty |
Yes |
repetition_penalty |
Yes |
logit_bias |
Yes |
top_k |
Yes |
min_p |
Yes |
seed |
Yes |
top_a |
Yes |
logprobs |
Yes |
top_logprobs |
Yes |
Use Cases
- Creative Writing: Novel writing, short stories, poetry
- Roleplay: Character-driven conversations and scenarios
- Dialogue Generation: Natural, engaging conversations
- Narrative Content: Blog posts, articles with storytelling elements
- Interactive Fiction: Text-based games and adventures
Limitations
- No vision/image input support
- No tool/function calling support
- No reasoning/chain-of-thought capabilities
- Context limited to 16,384 tokens (vs 32,768 in base model)
- Maximum completion limited to 2,048 tokens
Providers
| Provider |
Model Variant ID |
Notes |
| Mancer 2 |
magnum-72b-v4 |
Primary provider, FP8 quantization |
| Property |
Value |
| Model ID |
anthracite-org/magnum-v4-72b |
| Name |
Magnum v4 72B |
| Author |
anthracite-org |
| Created |
October 22, 2024 |
| Base Model |
Qwen2.5 72B |
| Instruction Format |
ChatML |
Feature Support
| Feature |
Supported |
| Tool/Function Calling |
No |
| Reasoning/Chain-of-Thought |
No |
| Vision/Image Input |
No |
| Structured Output |
No |
Default Stop Tokens
<|im_start|>
<|im_end|>
<|endoftext|>
Usage Examples
LangMart API (Python)
import requests
response = requests.post(
"https://api.langmart.ai/v1/chat/completions",
headers={
"Authorization": "Bearer YOUR_LANGMART_API_KEY",
"Content-Type": "application/json"
},
json={
"model": "anthracite-org/magnum-v4-72b",
"messages": [
{
"role": "user",
"content": "Write a short story about a mysterious lighthouse."
}
],
"max_tokens": 1024,
"temperature": 0.8
}
)
print(response.json()["choices"][0]["message"]["content"])
LangMart API (cURL)
curl https://api.langmart.ai/v1/chat/completions \
-H "Authorization: Bearer YOUR_LANGMART_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "anthracite-org/magnum-v4-72b",
"messages": [
{
"role": "user",
"content": "Write a short story about a mysterious lighthouse."
}
],
"max_tokens": 1024,
"temperature": 0.8
}'
LangMart API (JavaScript/Node.js)
const response = await fetch("https://api.langmart.ai/v1/chat/completions", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_LANGMART_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({
model: "anthracite-org/magnum-v4-72b",
messages: [
{
role: "user",
content: "Write a short story about a mysterious lighthouse."
}
],
max_tokens: 1024,
temperature: 0.8
})
});
const data = await response.json();
console.log(data.choices[0].message.content);
<|im_start|>system
You are a creative writing assistant specialized in crafting engaging narratives.
<|im_end|>
<|im_start|>user
Write a short story about a mysterious lighthouse.
<|im_end|>
<|im_start|>assistant
Recommended Settings
For creative writing and roleplay:
| Parameter |
Recommended Value |
temperature |
0.7 - 0.9 |
top_p |
0.9 - 0.95 |
top_k |
40 - 100 |
repetition_penalty |
1.1 - 1.15 |
max_tokens |
1024 - 2048 |
For more deterministic outputs:
| Parameter |
Recommended Value |
temperature |
0.3 - 0.5 |
top_p |
0.8 |
repetition_penalty |
1.05 |
Source