DeepHermes 3 Mistral 24B Preview

About DeepHermes 3 Mistral 24B Preview

DeepHermes 3 (Mistral 24B Preview) is an instruction-tuned language model by Nous Research based on Mistral-Small-24B, designed for chat, function calling, and advanced multi-turn reasoning. It introduces a dual-mode system that toggles between intuitive chat responses and structured “deep reasoning” mode using special system prompts. Fine-tuned via distillation from R1, it supports structured output (JSON mode) and function call syntax for agent-based applications. DeepHermes 3 supports a **reasoning toggle via system prompt**, allowing users to switch between fast, intuitive responses and deliberate, multi-step reasoning. When activated with the following specific system instruction, the model enters a *"deep thinking"* mode—generating extended chains of thought wrapped in `<think></think>` tags before delivering a final answer. System Prompt: You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the problem and deliberate with yourself via systematic reasoning processes to help come to a correct solution prior to answering. You should enclose your thoughts and internal monologue inside <think> </think> tags, and then provide your solution or response to the problem.

Model Specifications

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

Nous Research Model Lineup

Compare all models from Nous Research to find the best fit

Similar Models from Other Providers

Cross-brand alternatives with similar capabilities

Qwen2.5 Coder 7B Instruct

Alibaba Qwen

Input: $0.03

Output: $0.09

Context: 33k

Gemma 2 9B

Google

Input: $0.03

Output: $0.09

Context: 8k

MythoMax 13B

Gryphe

Input: $0.06

Output: $0.06

Context: 8k

gpt-oss-20b

OpenAI

Input: $0.02

Output: $0.10

Context: 131k

💡 Cheaper Alternatives

Same Brand (Nous Research)

Cross Brand

🚀 Quick Start

Get started with DeepHermes 3 Mistral 24B Preview API

from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="nousresearch/deephermes-3-mistral-24b-preview",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)

Continue Your Decision