--- title: Llama 3 Instruct (8B)—Top-tier AI for content creation, query resolution, and more canonical: https://telnyx.com/llm-library/llama-3-instruct-8b --- # Llama 3 Instruct (8B)—Top-tier AI for content creation, query resolution, and more [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.) Llama 3 Instruct (8B)—Top-tier AI for content creation, query resolution, and more # Llama 3 Instruct 8B Meta's 8B-parameter Llama 3 model, instruction-tuned for assistant-style dialogue with improved performance over Llama 2 across standard benchmarks. [Start building](https://telnyx.com/sign-up)[GET Available Models](https://developers.telnyx.com/docs/inference/models) ## about Trained on 15 trillion tokens, a 7.5x increase over Llama 2, the 8B model matches [Llama 2 70B on MMLU at 68.4%](https://ai.meta.com/blog/meta-llama-3/) with 9x fewer parameters. It introduced a new tiktoken-based tokenizer with 128K vocabulary that produces 15% fewer tokens for English text, and shifted from PPO to Direct Preference Optimization for alignment. Licensellama3 Context window(in thousands)8192 ## 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 Llama 3 Instruct 8B In the [AI Playground](https://portal.telnyx.com/#/app/next/ai/ai-playground "Telnyx AI Playground") select Llama 3 Instruct 8B 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 ### What is Llama 3 8B Instruct? Llama 3 8B Instruct is Meta's instruction-tuned 8 billion parameter model from the original Llama 3 release in April 2024\. It is available through [Telnyx's inference platform](https://telnyx.com/llm-library/llama-3-instruct-8b) and on Hugging Face. ### What is the difference between Llama 3 8B and 8B Instruct? The base Llama 3 8B is trained for next-token prediction, while the Instruct variant is fine-tuned for following instructions and dialogue. For most applications, the [Instruct version](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) is recommended. ## Use cases for Llama 3 Instruct 8B 1. **Efficiency-first deployment:** Matching Llama 2 70B at 68.4% MMLU with 9x fewer parameters, it provides 70B-class quality on single-GPU hardware for latency-sensitive applications. 2. **Code generation:** Scoring 62.2% on HumanEval versus Llama 2 70B's 29.9%, it handles code completion and generation tasks that previously required models an order of magnitude larger. 3. **DPO-aligned conversational agents:** Trained with Direct Preference Optimization instead of PPO, it provides stable, well-calibrated dialogue for assistant-style applications without the training instability of reinforcement learning. ## Quality Arena Elo1152 MMLU68.4 MT BenchN/A Llama 3 8B Instruct scores 67.4% on MMLU (5-shot), matching Llama 2 70B Chat (68.9%) with 9x fewer parameters on the same sheet. On HumanEval it reaches 62.2% versus Llama 2 70B's 29.9%, a dramatic code generation improvement. Trained on 15T tokens (7.5x more than Llama 2), it proved that data scale can substitute for parameter count. **GPT-4** 1165 **GPT-4 0613** 1163 **Llama 3 Instruct 8B** 1152 **Claude-Sonnet-4-20250514** 1138 **GPT-3.5 Turbo-0613** 1117 ## pricing The cost per 1,000 tokens for the Llama 3 Instruct (8B) model with Telnyx Inference is $0.0002\. For instance, if an enterprise were to analyze 1,000,000 customer chats, each averaging 1,000 tokens, the total cost would be $200. ## What's Twitter saying? * Developers praise Llama 3 8B Instruct's **insane benchmarks**, nearly matching Llama 2 70B and outperforming Mistral 7B, with strong instruction tuning ready for immediate use. * Benchmarks show it excels in MMLU (69.4), HumanEval code (72.6), and GSM8K math (84.5), beating Gemma 2–9B and Mistral–7B in most categories. * Some tech testers report **disappointing real-world results** despite benchmarks, calling it a "huge step backwards" with weird, random outputs in practice. | 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 is Llama 3.1 8B Instruct good for? Llama 3 8B Instruct handles conversational AI, code generation, and summarization tasks well at low compute cost. It is a practical choice for [production deployments](https://telnyx.com/llm-library/llama-3-instruct-8b) that need efficient inference. ### Is Llama 3 8B free? Yes, Llama 3 8B is released under Meta's community license for free commercial use. Weights are available on [Hugging Face](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) for download. ### How does Llama 3 8B compare to Llama 3.1 8B? Llama 3.1 8B expands the context window from 8K to 128K tokens and adds multilingual support. For new projects, [Llama 3.1 8B](https://telnyx.com/llm-library/gpt-4-0613) is the better choice with its improved capabilities. ### What GPU do I need for Llama 3 8B? Llama 3 8B requires about 16GB of VRAM at full precision or 8GB with quantization. An RTX 3070 or above handles the quantized version for [local development](https://telnyx.com/llm-library/llama-3-instruct-8b).