--- title: GPT-4 32K—Chat with this model canonical: https://telnyx.com/llm-library/gpt-4-32k --- # GPT-4 32K—Chat with this model [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.) GPT-4 32K—Chat with this model # GPT-4 32K OpenAI's multimodal model with human-level performance on professional benchmarks, supporting text and image inputs with strong reasoning across complex tasks. [Start building](https://telnyx.com/sign-up)[GET Available Models](https://developers.telnyx.com/docs/inference/models) ## about This variant extended [GPT-4's context window](https://developers.openai.com/docs/models/gpt-4) to 32,768 tokens at twice the per-token cost of standard GPT-4, making it the most expensive chat model OpenAI offered. Access remained restricted behind a separate waitlist even after GPT-4 API access was broadly available in July 2023, and it was effectively made obsolete by GPT-4 Turbo's 128K context at a lower price point four months later. Licenseopenai 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 ### NVIDIA-NemotronLabs-VoiceChat-11B ### 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 GPT-4 32K In the [AI Playground](https://portal.telnyx.com/#/app/next/ai/ai-playground "Telnyx AI Playground") select GPT-4 32K 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 the difference between GPT-4 and GPT-4 32K? GPT-4 32K extends the standard 8K context window to 32,768 tokens for processing longer documents. The underlying model is identical, with the [larger context](https://telnyx.com/llm-library/gpt-4-32k) being the only difference. ### How much is GPT-4 32K Azure? GPT-4 32K on Azure costs $60 per million input tokens and $120 per million output tokens. [Inference providers](https://telnyx.com/llm-library/gpt-4-32k-0314) offer alternative access with their own pricing. ### Why is GPT-4 going away? OpenAI is retiring older GPT-4 snapshots as newer models offer better performance at lower cost. GPT-4o, GPT-4.1, and GPT-5 have for most applications. 128000 ## Use cases for GPT-4 32K 1. **Full-document contract analysis:** The 32,768-token context window accommodates entire lease agreements, insurance policies, and regulatory filings for clause-by-clause review in a single prompt. 2. **Extended technical dialogue:** Retaining 32K tokens of conversation history enables sustained multi-turn interactions for architectural design, debugging sessions, and research discussions without context loss. 3. **Multi-file code review:** It ingests multiple source files simultaneously for cross-file dependency analysis, interface validation, and consistency checking across larger codebases. ## Quality Arena EloN/A MMLUN/A MT BenchN/A GPT-4 32k shares the same 86.4% MMLU (5-shot) and 8.99 MT-Bench scores as the standard GPT-4 on the sheet, differing only in its 32,768-token context window. The 32k variant was one of the rarest OpenAI models, restricted behind a separate waitlist even after GPT-4 API access opened broadly. It was superseded by GPT-4 Turbo (128K context) within months of its limited release. **Claude-Opus-4-6** 1501 **GLM-5** 1456 **gpt-5.1** 1455 **Kimi-K2.5** 1454 **gpt-5.2** 1440 ## pricing Running GPT-4 32k through Telnyx Inference costs $60.00 per million input tokens and $120.00 per million output tokens. Processing 100,000 long documents at 20,000 tokens each would cost approximately $120,000 input plus $240,000 output. GPT-4 Turbo ($10/$30 per million tokens) on the same sheet offers 4x the context window at one-sixth the cost. ## What's Twitter saying? * Developers praise **GPT-4 32k's coding prowess**, noting it's phenomenal for generating and tweaking code, enabling ambitious projects without dependencies, though some distrust it for complex tasks due to debugging issues. * Reviewers highlight its **superior performance** over GPT-3.5 in benchmarks like exams and code understanding, but criticize slower speeds, higher costs (e.g., $15k for 100k requests), and occasional hallucinations. * Community discussions question **GPT-4 32k access legitimacy** on platforms like Poe, suspecting scams or beta limitations, while noting rollout excitement for longer context in conversations and tasks. | 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 | NVIDIA-NemotronLabs-VoiceChat-11B | speech to-speech | English | 8,192 | 11.1B | medium | openmdw-1.1 | | 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) superseded the original GPT-4 ### What is GPT-4 128K? GPT-4 128K refers to GPT-4 Turbo, which expanded the context window from 32K to 128,000 tokens. It also added JSON mode and reduced pricing compared to [GPT-4 32K](https://openai.com/index/gpt-4-research/). ### Is GPT-4 32K still worth using? GPT-4 32K has been superseded by GPT-4 Turbo (128K), GPT-4o, and GPT-4.1 (1M context). Unless you have specific version requirements, [newer models](https://telnyx.com/llm-library/gpt-4-32k) offer better performance at lower cost. ### How does GPT-4 32K compare to GPT-4 Turbo? GPT-4 Turbo offers a 128K context window at roughly one-third the price of GPT-4 32K, with additional features like JSON mode. [GPT-4 Turbo](https://telnyx.com/llm-library/gpt-4-32k-0314) is the clear upgrade for applications using GPT-4 32K.