--- title: "Claude Sonnet 4: Advanced Reasoning and Writing Model" canonical: https://telnyx.com/llm-library/claude-sonnet-4-20250514 --- # Claude Sonnet 4: Advanced Reasoning and Writing 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.) # Claude-Sonnet-4-20250514 Anthropic's Claude Sonnet 4, delivering strong results in reasoning, coding, multilingual tasks, and long-context handling with a balanced speed-to-quality ratio. [Start building](https://telnyx.com/sign-up)[GET Available Models](https://developers.telnyx.com/docs/inference/models) ## about Scoring 72.7% on SWE-bench Verified at launch, [Sonnet 4](https://www.anthropic.com/news/claude-4) introduced extended thinking for step-by-step problem decomposition and parallel tool execution within a 200K context window. Subsequent updates at the same $3/$15 price point pushed agentic coding to 77.2% (Sonnet 4.5) and 79.6% (Sonnet 4.6), establishing the Sonnet tier as Anthropic's fastest-improving model line. Licenseanthropic 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 Claude-Sonnet-4-20250514 In the [AI Playground](https://portal.telnyx.com/#/app/next/ai/ai-playground "Telnyx AI Playground") select Claude-Sonnet-4-20250514 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 Claude Sonnet 4 better than GPT 4? Claude Sonnet 4 outperforms the original GPT-4 on most benchmarks and is competitive with newer models like GPT-4o and GPT-4.1\. It is particularly strong on [coding and instruction-following tasks](https://telnyx.com/llm-library/claude-sonnet-4-20250514) where nuanced understanding of context matters. ### What is Claude Sonnet 4? Claude Sonnet 4 is Anthropic's flagship production model, released in May 2025 as part of the [Claude 4 model family](https://www.anthropic.com/news/claude-4). It balances strong reasoning capability with practical latency and cost for real-world deployments. 200000 ## Use cases for Claude-Sonnet-4-20250514 1. **Agentic code repair:** At 72.7% on SWE-bench Verified with parallel tool execution, Sonnet 4 autonomously diagnoses, patches, and tests bugs across multi-file repositories. 2. **Extended document analysis:** The 200K context window combined with extended thinking mode enables it to process and reason over full codebases, legal filings, or research corpora in one pass. 3. **Multilingual content localization:** Strong multilingual benchmark performance makes it effective for translating and adapting technical documentation while preserving domain-specific terminology. ## Quality Arena Elo1138 MMLU77.2 MT Bench89.5 Claude Sonnet 4 scores 86.5% on MMLU and 72.7% on SWE-bench Verified at launch, placing it between GPT-4 Turbo (86.5% MMLU) and Claude 3.7 Sonnet (86.1% MMLU) on general knowledge while significantly outperforming both on coding tasks. Subsequent updates at the same price point pushed SWE-bench to 79.6% (Sonnet 4.6), making it the fastest-improving model line at this tier. **GPT-4 0613** 1163 **Llama 3 Instruct 8B** 1152 **Claude-Sonnet-4-20250514** 1138 **GPT-3.5 Turbo-0613** 1117 **Mixtral 8x7B Instruct v0.1** 1114 ## pricing Running Claude Sonnet 4 through Telnyx Inference costs $3.00 per million input tokens and $15.00 per million output tokens. Analyzing 1,000,000 code reviews at 2,000 tokens each would cost approximately $18,000, roughly 40% less than Claude Opus 4.6 ($25,000) for workloads where Sonnet-tier reasoning is sufficient. ## What's Twitter saying? * **Exceptional coding performance**: [Claude Sonnet 4 achieved a \*\*72.7%](https://www.helicone.ai/blog/claude-opus-and-sonnet-4-full-developer-guide) score on SWE-bench Verified\*\*, outperforming competitors like GPT-4.1 (54.6%) and Gemini 2.5 Pro (63.2%), with developers confirming these benchmarks translate to "remarkable real-world capabilities" in practical software engineering tasks. * **Superior UI/design generation**: [In head-to-head testing, Claude Sonnet 4](https://www.datacamp.com/blog/claude-4) produced **clean layouts with professional styling**, significantly outperforming GPT-4.1's poor dark mode handling and Gemini 2.5 Pro's overly bright design choices. * **Excellent value as a free model**: [Tech reviewers emphasize that Sonnet 4](https://www.anthropic.com/news/claude-4) is "very-very impressive" for a free-tier model, delivering "an optimal mix of capability and practicality" suitable for 90% of typical AI use cases like drafting emails, fixing code, and summarizing documents. | 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) ### Why is Claude Sonnet 4 so good? Claude Sonnet 4 excels due to Anthropic's focus on instruction following, reduced hallucination, and strong performance on agentic coding tasks. It consistently ranks among the top models on [SWE-bench and other coding benchmarks](https://www.anthropic.com/claude/sonnet), making it a preferred choice for developer workflows. ### Is Claude Sonnet 4 paid? Claude Sonnet 4 is available for free with usage limits on claude.ai, and through the API at $3 per million input tokens and $15 per million output tokens. Infrastructure providers like [Telnyx offer API access](https://telnyx.com/llm-library/claude-sonnet-4-20250514) with co-located inference for reduced latency. ### Is the Claude 4 Sonnet free? Claude Sonnet 4 is free with usage limits on claude.ai. API access requires a paid account, with pricing at $3/$15 per million tokens for input/output. [Hosted inference platforms](https://telnyx.com/resources/voice-ai-optimization-stack-templates) provide alternative access points with their own pricing. ### Is Grok better at coding than Claude? Claude Sonnet 4 generally outperforms Grok on coding benchmarks, particularly on SWE-bench Verified and agentic coding tasks. Grok has strengths in real-time information access, but for [code generation and refactoring](https://telnyx.com/llm-library/claude-sonnet-4-20250514), Claude Sonnet 4 is the stronger choice. ### Is claude.ai better than ChatGPT? Claude and ChatGPT each have advantages depending on the task. Claude Sonnet 4 tends to excel on [coding, writing, and instruction following](https://telnyx.com/llm-library/claude-sonnet-4-20250514), while ChatGPT (GPT-5) has broader tool integration with web search, image generation, and plugins. Claude Sonnet 4: Advanced Reasoning and Writing Model