--- title: DeepSeek Coder 6.7B Instruct—Chat with the LLM canonical: https://telnyx.com/llm-library/deepseek-coder-6-7b-instruct --- # DeepSeek Coder 6.7B Instruct—Chat with the LLM [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.) # DeepSeek Coder 6.7B Instruct A 6.7B-parameter code model from DeepSeek trained on 87% code data, fine-tuned for instruction-based code generation, completion, and refactoring tasks. [Start building](https://telnyx.com/sign-up)[GET Available Models](https://developers.telnyx.com/docs/inference/models) ## about Trained from scratch on a 2 trillion-token corpus split 87% code and 13% natural language across 87 programming languages, this model punches well above its weight class. At just 6.7B parameters, it matches [CodeLlama-34B on HumanEval](https://github.com/deepseek-ai/DeepSeek-Coder) with 66.1% pass@1, a model five times its size. Licensedeepseek Context window(in thousands)16384 ## 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 ### 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 DeepSeek Coder 6.7B Instruct In the [AI Playground](https://portal.telnyx.com/#/app/next/ai/ai-playground "Telnyx AI Playground") select DeepSeek Coder 6.7B Instruct 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 DeepSeek Coder?** DeepSeek Coder is a state-of-the-art code language model developed by DeepSeek AI, designed for high-performance code completion and infilling tasks. It is trained on 2T tokens, comprising 87% code from various programming languages and 13% natural language in both English and Chinese, available in multiple sizes ranging from 1.3B to 33B parameters. ### **How can I use DeepSeek Coder for my project?** To use DeepSeek Coder, you can integrate it into your project using the Hugging Face Transformers library. First, install the library, then load the model and tokenizer with the provided model name "deepseek-ai/deepseek-coder-6.7b-instruct". You can then input your code requirements, and the model will assist with code completion and infilling tasks. For detailed usage instructions, refer to the [model's homepage](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct). ## Use cases for DeepSeek Coder 6.7B Instruct 1. **Lightweight code completion in IDEs:** At 6.7B parameters, it runs locally on consumer GPUs while matching 34B-class models on HumanEval, enabling private, low-latency autocomplete. 2. **Automated code refactoring:** Trained on 87% code data across 87 programming languages, it restructures functions and simplifies logic while preserving behavior across language boundaries. 3. **Codebase documentation generation:** Its instruction-tuning on code-specific tasks allows it to read existing functions and produce accurate inline documentation and docstrings. ## Quality Arena EloN/A MMLUN/A MT BenchN/A DeepSeek Coder 6.7B Instruct scores 78.6% on HumanEval, outperforming Code Llama 70B Instruct (67.8%) on the same benchmark despite being 10x smaller. On MBPP it reaches 73.8%, confirming that the 87% code training data composition translates to strong code generation at efficient scale. Standard MMLU is not published for this code-focused model. **Claude-Opus-4-6** 1501 **GLM-5** 1456 **gpt-5.1** 1455 **Kimi-K2.5** 1454 **gpt-5.2** 1440 ## pricing The cost of running DeepSeek Coder 6.7B with Telnyx Inference is $0.0002 per 1,000 tokens. Generating code for 500,000 programming tasks at 1,000 tokens each would cost $100, compared to $500 for the same workload on a 70B-class code model. ## What's Twitter saying? * Developers on Hacker News praise DeepSeek Coder 6.7B as **vastly superior** to larger models like CodeLlama 7B and note its 1.3B variant is impressively capable, with fine-tunes like Magicoder offering slight improvements. * Benchmarks and reviews highlight its **state-of-the-art performance**, surpassing CodeLlama-34B on HumanEval despite fewer parameters and providing an excellent balance for mid-range hardware (16GB RAM). * A YouTube benchmark calls the quantized 6.7B instruct version **not that great** for tasks, leading to no recommendation, though it's runnable on low-end PCs. | 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 | | 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) ### **Is DeepSeek Coder suitable for commercial projects?** Yes, DeepSeek Coder supports commercial use under its Model License. The code repository is licensed under the MIT License, ensuring flexibility and freedom for commercial and private projects alike. For more details, review the [LICENSE-MODEL](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct/blob/main/LICENSE). ### **Can DeepSeek Coder be used for languages other than English?** Yes, DeepSeek Coder is trained on a dataset that includes both English and Chinese natural languages, making it suitable for code completion tasks in projects that involve these languages. It's designed to understand and generate code based on the context provided in either language. ### **How does DeepSeek Coder perform compared to other code models?** DeepSeek Coder achieves state-of-the-art performance among publicly available code models, outperforming others on several benchmarks, including HumanEval, MultiPL-E, MBPP, DS-1000, and APPS. Its training on a large corpus of 2T tokens with a significant percentage of code ensures superior model performance for a wide range of programming languages. ### **What model sizes are available for DeepSeek Coder?** DeepSeek Coder is available in various sizes to suit different project requirements and computational capabilities, including 1.3B, 5.7B, 6.7B, and 33B parameter models. This flexibility allows users to select the most suitable model size for their specific needs. ### **How do I report an issue or get support for DeepSeek Coder?** If you encounter any issues or have questions regarding DeepSeek Coder, you can raise an issue through the [Hugging Face repository](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) or contact the DeepSeek team directly at [\[email protected\]](https://telnyx.com/cdn-cgi/l/email-protection#7d1c1a14221e1219183d1918180d0e181816531e1210). The team is dedicated to providing support and ensuring users can effectively utilize the model for their coding projects. ### **Is the model too large for serverless deployment?** ### What is DeepSeek Coder 6.7B? DeepSeek Coder 6.7B is a code-focused language model trained from scratch on 2 trillion tokens, with a composition of 87% code and 13% natural language. The instruct variant is [fine-tuned for instruction-following tasks](https://telnyx.com/llm-library/deepseek-coder-6-7b-instruct) like code generation, completion, and refactoring across multiple programming languages. ### Can I use DeepSeek for coding? Yes, DeepSeek Coder models are specifically designed for coding tasks. They support code generation from natural language descriptions, code completion, debugging, and refactoring across languages including Python, Java, C++, and JavaScript. The models are available through [multiple deployment options](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) including local inference and hosted APIs. ### Which DeepSeek model is best for coding? For coding tasks, the DeepSeek Coder series outperforms the general-purpose DeepSeek models. The 33B instruct variant offers the strongest coding performance in the original series, while the newer [DeepSeek Coder V2](https://deepseekcoder.github.io/) models provide further improvements. The 6.7B variant offers a good balance between performance and resource efficiency for smaller deployments. ### What are the limitations of DeepSeek Coder? DeepSeek Coder has several known limitations including occasional hallucination of function names or APIs that don't exist, weaker performance on less common programming languages, and a 16K token context window that limits handling of very large codebases. These [practical constraints](https://www.digitalocean.com/resources/articles/deepseek-pros-and-cons) are important to consider for production use cases. ### What is DeepSeek Coder used for? DeepSeek Coder is used for automated code generation, code completion, bug detection, and code explanation tasks. Development teams use it for [accelerating prototyping and code automation](https://latenode.com/blog/latenode-platform/latenode-platform-overview/what-is-deepseek-coder-revolutionizing-code-automation-in-latenode) workflows. Its compact 6.7B size makes it practical for local deployment where latency and data privacy matter. ### Is DeepSeek Coder free? Yes, DeepSeek Coder is open-source and released under a permissive license that allows both research and commercial use. The model weights are [freely available on Hugging Face](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) and can be run locally using frameworks like Ollama, vLLM, or llama.cpp. ### Is DeepSeek better than GPT? DeepSeek Coder 6.7B is smaller and more specialized than GPT-4 or GPT-3.5 Turbo. On code-specific benchmarks, the larger DeepSeek Coder 33B matches GPT-3.5 Turbo on HumanEval. The tradeoff is between GPT's broader capabilities and [DeepSeek's open-source accessibility](https://github.com/deepseek-ai/DeepSeek-Coder) with the ability to self-host and fine-tune. DeepSeek Coder 6.7B Instruct—Chat with the LLM