---
title: Nous: Hermes 4 70B — Reasoning LLM | ModelsLab
description: Access Nous: Hermes 4 70B API for hybrid reasoning, math, coding, and JSON outputs. Generate precise responses via LLM endpoint now.
url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/nous-hermes-4-70b
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/nous-hermes-4-70b
type: website
component: Seo/ModelPage
generated_at: 2026-05-13T10:35:27.197274Z
---

Available now on ModelsLab · Language Model

Nous: Hermes 4 70B
Reason Hybrid, Respond Precise
---

[Try Nous: Hermes 4 70B](/models/open_router/nousresearch-hermes-4-70b) [API Documentation](https://docs.modelslab.com)

Toggle Reasoning, Master Tasks
---

Hybrid Mode

### Control Think Traces

Enable <think> tags for step-by-step reasoning or direct answers with reasoning boolean.

Schema Outputs

### JSON Function Calling

Produces valid JSON schemas, supports tool use and function calling for API integrations.

STEM Boost

### Math Code Logic

Excels in mathematics, coding, STEM, and logic via 60B token post-training corpus.

Examples

See what Nous: Hermes 4 70B can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/nousresearch-hermes-4-70b).

Math Proof

“Prove Fermat's Last Theorem for n=3 using step-by-step reasoning in <think> tags, then summarize the key steps in plain English.”

Code Debug

“Analyze this Python function for bugs: def factorial(n): if n == 0: return 1 else: return n \* factorial(n-1). Fix and optimize with reasoning enabled.”

JSON Schema

“Generate a weather API response in strict JSON schema: {location: string, temp: number, forecast: array}. Use Paris, France with reasoning for data logic.”

Logic Puzzle

“Solve Einstein's riddle: five houses, colors, nationalities, drinks, smokes, pets. Who owns the fish? Output structured steps then final answer.”

For Developers

A few lines of code.
Reasoning LLM. One Call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Nous: Hermes 4 70B
---

[Read the docs ](https://docs.modelslab.com)

### What is Nous: Hermes 4 70B?

Nous: Hermes 4 70B is a 70B parameter LLM from Nous Research on Llama-3.1-70B base. It features hybrid reasoning with 131k context. Released August 2025.

### How does Nous: Hermes 4 70B API work?

Access via LLM endpoint with reasoning boolean to toggle <think> traces. Supports JSON mode, schema adherence, function calling. Pricing starts at $0.13/M input tokens.

### What are Nous Hermes 4 70B strengths?

Improves math, coding, STEM, logic over Hermes 3 via 60B token corpus. Offers steerability, reduced refusals, tool use. Maintains general tasks like writing.

### Is Nous: Hermes 4 70B model open-weight?

Yes, fully open-weight for accessibility. Trained with synthetic data pipeline, no pre-training changes. Benchmarks high on math and refusal tasks.

### Nous: Hermes 4 70B alternative to what?

Alternative to closed models like GPT-4o via open API access. Matches frontier reasoning at lower cost. Use for structured outputs and hybrid mode.

### Nous Hermes 4 70b context length?

Supports 131,072 tokens. Handles long inputs for complex reasoning chains. Toggle reasoning for speed or depth control.

Ready to create?
---

Start generating with Nous: Hermes 4 70B on ModelsLab.

[Try Nous: Hermes 4 70B](/models/open_router/nousresearch-hermes-4-70b) [API Documentation](https://docs.modelslab.com)

---

*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

---
*Generated by ModelsLab - 2026-05-13*