--- title: Nous Hermes 2 Mistral 7B—Quality and performance breakdown canonical: https://telnyx.com/llm-library/nous-hermes-2-mistral-7b-dpo --- # Nous Hermes 2 Mistral 7B—Quality and performance breakdown [Start building](https://telnyx.com/sign-up) ### Ask AI * [![GPT](https://d2efw2akbx8gaf.cloudfront.net/https://dotcom-payload-assets-prod.s3.us-east-1.amazonaws.com/cms-media/chatgpt_icon-ea55e09d.jpeg?width=92&format=webp)](https://chat.openai.com/?q=What makes Telnyx's global network different, breakdown call quality for normal phone calls and voice AI calls.) * [![Claude](https://d2efw2akbx8gaf.cloudfront.net/https://dotcom-payload-assets-prod.s3.us-east-1.amazonaws.com/cms-media/claude_icon-c7c8eef3.webp?width=92&format=webp)](https://claude.ai/new?q=What makes Telnyx's global network different, breakdown call quality for normal phone calls and voice AI calls.) * [![Perplexity](https://d2efw2akbx8gaf.cloudfront.net/https://dotcom-payload-assets-prod.s3.us-east-1.amazonaws.com/cms-media/perplexity_icon-cd5b74f1.webp?width=92&format=webp)](https://www.perplexity.ai/search?q=What makes Telnyx's global network different, breakdown call quality for normal phone calls and voice AI calls.) * [![Gemini](https://d2efw2akbx8gaf.cloudfront.net/https://dotcom-payload-assets-prod.s3.us-east-1.amazonaws.com/cms-media/gemini_icon-4ff1cbf4.webp?width=92&format=webp)](https://www.google.com/search?udm=50&aep=11&q=What makes Telnyx's global network different, breakdown call quality for normal phone calls and voice AI calls.) * [![Grok](https://d2efw2akbx8gaf.cloudfront.net/https://dotcom-payload-assets-prod.s3.us-east-1.amazonaws.com/cms-media/grok_icon-e588e5bd.webp?width=92&format=webp)](https://x.com/i/grok?text=What makes Telnyx's global network different, breakdown call quality for normal phone calls and voice AI calls.) # Nous Hermes 2 Mistral 7B A 7B model from Nous Research fine-tuned with Direct Preference Optimization, strong in instruction-following, summarization, and code generation tasks. [Start building](https://telnyx.com/sign-up)[GET Available Models](https://developers.telnyx.com/docs/inference/models) ## about Nous Research applied a two-stage training process to Mistral 7B, first fine-tuning on roughly one million [GPT-4-generated synthetic instructions](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO) via the OpenHermes dataset, then aligning with Direct Preference Optimization. It uses the ChatML prompt format for structured multi-turn dialogue and runs in under 5GB of VRAM with 4-bit quantization. Licenseapache-2.0 Context window(in thousands) ## Explore Our LLM Library Discover the power and diversity of large language models available with Telnyx. Explore the options below to find the perfect model for your project. ### DeepSeek-V4-Flash-0731 OrganizationTelnyx Model NameDeepSeek-V4-Flash-0731 Taskstext generation Languages SupportedEnglish Context Length1,048,576 Parameters284.0B Model Tierunlisted Licensemit ### DeepSeek-V4.1-Flash ### gemma-2b-it ### gemma-4-26B-A4B-it ### gemma-4-31B-it ### Llama-3.3-70B-Instruct ### Meta-Llama-3.1-70B-Instruct ### Meta-Llama-3.1-8B-Instruct ### MiniMax-M2.7 ### MiniMax-M3-MXFP8 ### Kimi-K2.5 ### Kimi-K2.6 ### Kimi-K3 ### personaplex-7b-v1 ### Laguna-S-2.1 ### Qwen3-235B-A22B ### Qwen3.8-27B ### GLM-5.1-FP8 ### GLM-5.2 ### GLM-5.3 ### GLM-5.3-Flash ### claude-haiku-4-5 ### gemini-2.5-flash ### gemini-3.7-flash ### gpt-oss-120b ### gpt-4.1 ### gpt-4o ### gpt-4o-mini ### gpt-5 ### gpt-5.1 ### gpt-5.2 ### gpt-5.4 ### gpt-5.4-mini ### gpt-5.6-luna ### gpt-5.6-sol ### gpt-live-1 HOW IT WORKS ## Selecting LLMs for Voice AI [GET Available Models](https://developers.telnyx.com/docs/inference/models) ### Create an account Sign-up to the Telnyx platform to get access to our suite of intuitive AI tools. ### Choose Nous Hermes 2 Mistral 7B In the [AI Playground](https://portal.telnyx.com/#/app/next/ai/ai-playground "Telnyx AI Playground") select Nous Hermes 2 Mistral 7B from the dropdown. ### Enter your API key If you’re using a proprietary model, you’ll need your API key before prompting the LLM. Our vast selection of OS models allow you to get started right away. ### Prompt the LLM Get responses from an LLM in minutes, and scale with our [OpenAI-compatible APIs](https://developers.telnyx.com/docs/inference/getting-started "Inference API Quickstart"). Step 1/4 **RESOURCES** ## Get started Check out our helpful tools to help get you started. * ### Test in the portal Easily browse and select your preferred model in the AI Playground. [Test today](https://portal.telnyx.com/#/ai/assistants) ## Sign up and start building [Sign up](https://telnyx.com/sign-up)[Contact sales](https://telnyx.com/contact-us) ## faqs ### Is Mistral 7B a good model? Nous Hermes 2 Mistral 7B DPO builds on the strong Mistral 7B base with DPO alignment training, improving instruction following and reducing harmful outputs. It is a [competitive open-weight model](https://telnyx.com/llm-library/nous-hermes-2-mistral-7b-dpo) for chat and reasoning tasks at the 7B scale. ### Is the Mistral 7B decoder only? Yes, Mistral 7B uses a decoder-only transformer architecture, which is standard for autoregressive text generation models. Nous Hermes 2 inherits this architecture and adds [DPO-based alignment](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO) for improved instruction following. 32768 ## Use cases for Nous Hermes 2 Mistral 7B 1. **Structured dialogue systems:** The ChatML prompt format enables precise system/user/assistant role separation, making it reliable for multi-turn agents that require consistent persona adherence. 2. **Low-resource deployment:** Running in under 5GB VRAM with 4-bit quantization, it serves as an instruction-following model on consumer hardware and edge devices. 3. **Synthetic data generation:** DPO alignment on GPT-4-generated instructions makes it effective at producing training data for downstream models that need diverse, high-quality instruction-response pairs. ## Quality Arena Elo1010 MMLU55.4 MT Bench6.84 Nous Hermes 2 Mistral 7B DPO scores 63.4% on MMLU, a 3-point improvement over the base Mistral 7B Instruct v0.1 (56.3%) on the same sheet after DPO alignment on GPT-4-generated instruction data. It trails Gemma 7B IT (64.3%) by about 1 point on MMLU but runs in under 5GB VRAM with 4-bit quantization, offering a trade-off between benchmark quality and deployment efficiency. **Gemma 7B IT** 1038 **Llama 2 Chat 7B** 1037 **Nous Hermes 2 Mistral 7B** 1010 **Mistral 7B Instruct v0.1** 1008 **Gemma 2B IT** 990 ## pricing The cost of running the model with Telnyx Inference is $0.0002 per 1,000 tokens. For instance, analyzing 1,000,000 customer chats, assuming each chat is 1,000 tokens long, would cost $200. ## What's Twitter saying? * Developers praise **Nous Hermes 2 Mistral 7B DPO** for superior benchmark performance over predecessors and rivals in reasoning, instruction following, and code generation tasks. * Tech reviews highlight its **efficiency** with low latency (0.61s), high throughput (93.91 tokens/s), and cost-effectiveness for developers as an AI co-pilot. * Community testers on YouTube report using it as their **main local LLM driver** for a month, testing it extensively in Obsidian AI suites with positive daily integration. | Organization | Model Name | Tasks | Languages Supported | Context Length | Parameters | Model Tier | License | | ------------ | ----------------------------------------------------------------------- | ---------------- | ------------------- | -------------- | ---------- | ---------- | ------------------------- | | Telnyx | DeepSeek-V4-Flash-0731 | text generation | English | 1,048,576 | 284.0B | unlisted | mit | | Telnyx | DeepSeek-V4.1-Flash | text generation | English | 1,048,576 | 552.0B | small | mit | | google | [gemma-2b-it](https://telnyx.com/llm-library/gemma-2b-it) | text generation | English | 8,192 | 2.5B | small | gemma | | google | gemma-4-26B-A4B-it | text to-text | Multilingual | 262,144 | 25.8B | small | apache-2.0 | | google | gemma-4-31B-it | text generation | Multilingual | 131,072 | 30.7B | small | apache-2.0 | | meta-llama | [Llama-3.3-70B-Instruct](https://telnyx.com/llm-library/llama-3.3-70b-instruct) | text generation | Multilingual | 99,000 | 70.6B | large | llama3.3 | | meta-llama | [Meta-Llama-3.1-70B-Instruct](https://telnyx.com/llm-library/meta-llama-3-1-70b-instruct) | text generation | Multilingual | 99,000 | 70.6B | large | llama3.1 | | meta-llama | [Meta-Llama-3.1-8B-Instruct](https://telnyx.com/llm-library/meta-llama-3.1-8b-instruct) | text generation | Multilingual | 131,072 | 8.0B | small | llama3.1 | | minimaxai | MiniMax-M2.7 | text generation | Multilingual | 200,000 | 0 | large | minimaxai | | minimaxai | MiniMax-M3-MXFP8 | text generation | Multilingual | 1,000,000 | 428.0B | small | minimax-community | | moonshotai | [Kimi-K2.5](https://telnyx.com/llm-library/kimi-k2.5) | text generation | Multilingual | 256,000 | 1.0T | large | modified-mit | | moonshotai | Kimi-K2.6 | text generation | Multilingual | 262,144 | 1.0T | medium | modified-mit | | moonshotai | Kimi-K3 | text generation | English | 1,000,000 | 2.8M | large | MIT Modified | | nvidia | personaplex-7b-v1 | speech to-speech | English | 3,000 | 7.0B | small | nvidia-open-model-license | | poolside | Laguna-S-2.1 | text generation | English | 1,048,576 | 117.6B | unlisted | OpenMDW-1.1 | | Qwen | [Qwen3-235B-A22B](https://telnyx.com/llm-library/qwen3-235b-a22b) | text generation | English | 32,768 | 235.1B | large | apache-2.0 | | Telnyx | Qwen3.8-27B | text generation | English | 262,144 | 27.0B | small | Apache 2.0 | | zai-org | GLM-5.1-FP8 | text generation | Multilingual | 202,752 | 753.9B | large | mit | | zai-org | GLM-5.2 | text generation | English | 1,000,000 | 753.9B | medium | MIT | | Telnyx | GLM-5.3 | text generation | English | 1,048,576 | 753.0B | medium | glm-5.3 | | zai-org | GLM-5.3-Flash | text generation | English | 1,048,576 | 320.0B | small | mit | | anthropic | [claude-haiku-4-5](https://telnyx.com/llm-library/claude-haiku-4-5) | text generation | Multilingual | 400,000 | 0 | large | openai | | google | [gemini-2.5-flash](https://telnyx.com/llm-library/gemini-2.5-flash) | text generation | Multilingual | 400,000 | 0 | large | openai | | google | gemini-3.7-flash | text generation | Multilingual | 400,000 | 0 | large | openai | | groq | [gpt-oss-120b](https://telnyx.com/llm-library/gpt-oss-120b) | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-4.1 | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | [gpt-4o](https://telnyx.com/llm-library/gpt-4-omni) | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | [gpt-4o-mini](https://telnyx.com/llm-library/gpt-4o-mini) | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5 | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5.1 | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | [gpt-5.2](https://telnyx.com/llm-library/gpt-5.2) | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5.4 | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5.4-mini | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5.6-luna | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-5.6-sol | text generation | Multilingual | 400,000 | 0 | large | openai | | openai | gpt-live-1 | speech to-speech | Multilingual | 400,000 | 0 | large | openai | * ### Explore the docs Don’t wait to scale, start today with our public API endpoints. [Get started](https://developers.telnyx.com/api-reference/assistants/list-assistants) * ### Stay up to date Keep an eye on our AI changelog so you don't miss a beat. [See updates](https://telnyx.com/release-notes) ### What does 7B mean in Mistral 7B? 7B refers to 7 billion parameters, which defines the model's size and capacity. Nous Hermes 2 Mistral 7B DPO uses all 7.3 billion parameters of the base model while adding alignment training that improves its behavior as a [conversational assistant](https://telnyx.com/llm-library/nous-hermes-2-mistral-7b-dpo). ### What is the maximum length of Mistral 7B? The base Mistral 7B architecture supports a 32K token context window using sliding window attention. Nous Hermes 2 Mistral 7B DPO inherits this capacity, making it suitable for [moderate-length document processing](https://telnyx.com/llm-library/nous-hermes-2-mixtral-8x7b) and multi-turn conversations. ### What is DPO training? Direct Preference Optimization (DPO) is an alignment technique that trains models to prefer helpful, accurate responses over harmful or incorrect ones without needing a separate reward model. Nous Research applied DPO to produce a [better-aligned variant](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO) of Mistral 7B for instruction-following tasks. ### How does Nous Hermes 2 compare to base Mistral 7B? Nous Hermes 2 significantly improves on base Mistral 7B for instruction following, chat quality, and task completion. The DPO alignment makes it more reliable for [production conversational applications](https://telnyx.com/llm-library/nous-hermes-2-mistral-7b-dpo) while maintaining the base model's efficiency. Nous Hermes 2 Mistral 7B—Quality and performance breakdown