about
Scoring 72.7% on SWE-bench Verified at launch, Sonnet 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)200000
Use cases for Claude-Sonnet-4-20250514
- 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.
- 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.
- 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.
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% 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 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 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.
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.
| Organization | Model Name | Tasks | Languages Supported | Context Length | Parameters | Model Tier | License |
|---|---|---|---|---|---|---|---|
| deepseek-ai | DeepSeek-R1-Distill-Qwen-14B | text generation | English | 43,000 | 14.8B | medium | deepseek |
| fixie-ai | ultravox-v0_4_1-llama-3_1-8b | audio text-to-text | Multilingual | 8,000 | 8.7B | small | mit |
| gemma-2b-it | text generation | English | 8,192 | 2.5B | small | gemma | |
| gemma-7b-it | text generation | English | 8,192 | 8.5B | small | gemma | |
| meta-llama | Llama-3.3-70B-Instruct | text generation | Multilingual | 99,000 | 70.6B | large | llama3.3 |
| meta-llama | Llama-Guard-3-1B | safety classification | Multilingual | 128,000 | 1.5B | small | llama3.3 |
| meta-llama | Meta-Llama-3.1-70B-Instruct | text generation | Multilingual | 99,000 | 70.6B | large | llama3.1 |
| meta-llama | Meta-Llama-3.1-8B-Instruct | text generation | Multilingual | 131,072 | 8.0B | small | llama3.1 |
| minimaxai | MiniMax-M2.5 | text generation | English | 2,000,000 | 0 | large | minimaxai |
| minimaxai | MiniMax-M2.7 | text generation | English | 200,000 | 0 | large | minimaxai |
| mistralai | Mistral-7B-Instruct-v0.1 | text generation | English | 8,192 | 7.2B | small | apache-2.0 |
| mistralai | Mistral-7B-Instruct-v0.2 | text generation | English | 32,768 | 7.2B | small | apache-2.0 |
| mistralai | Mixtral-8x7B-Instruct-v0.1 | text generation | Multilingual | 32,768 | 46.7B | medium | apache-2.0 |
| moonshotai | Kimi-K2.5 | text generation | English | 256,000 | 1.0T | large | modified-mit |
| Qwen | Qwen3-235B-A22B | text generation | English | 32,768 | 235.1B | large | apache-2.0 |
| zai-org | GLM-5.1-FP8 | text generation | English | 202,752 | 753.9B | large | mit |
| anthropic | claude-3-7-sonnet-latest | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-haiku-4-5 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-opus-4-6 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| anthropic | claude-sonnet-4-20250514 | text generation | Multilingual | 200,000 | 0 | large | anthropic |
| gemini-2.0-flash | text generation | Multilingual | 1,048,576 | 0 | large | ||
| gemini-2.5-flash | text generation | Multilingual | 1,048,576 | 0 | large | ||
| gemini-2.5-flash-lite | text generation | Multilingual | 1,048,576 | 0 | large | ||
| groq | gpt-oss-120b | text generation | English | 131,072 | 117.0B | large | groq |
| groq | kimi-k2-instruct | text generation | English | 131,072 | 1.0T | large | groq |
| groq | llama-3.3-70b-versatile | text generation | Multilingual | 131,072 | 70.6B | large | llama3.3 |
| groq | llama-4-maverick-17b-128e-instruct | text generation | Multilingual | 1,000,000 | 400.0B | large | llama4 |
| groq | llama-4-scout-17b-16e-instruct | text generation | Multilingual | 128,000 | 109.0B | large | llama4 |
| openai | gpt-3.5-turbo | text generation | Multilingual | 4,096 | 0 | large | openai |
| openai | gpt-4 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0125-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0314 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-0613 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-1106-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-32k-0314 | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4-turbo-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4.1 | text generation | Multilingual | 1,047,576 | 0 | large | openai |
| openai | gpt-4.1-mini | text generation | Multilingual | 1,047,576 | 0 | large | openai |
| openai | gpt-4o | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-4o-mini | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | gpt-5 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5-mini | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5.1 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | gpt-5.2 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | o1-mini | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | o1-preview | text generation | Multilingual | 128,000 | 0 | large | openai |
| openai | o3-mini | text generation | Multilingual | 200,000 | 0 | large | openai |
| xai-org | grok-2 | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-2-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3 | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-beta | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast-beta | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-fast-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-latest | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-mini | text generation | Multilingual | 131,072 | 0 | large | xai |
| xai-org | grok-3-mini-fast | text generation | Multilingual | 131,072 | 0 | large | xai |
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faqs
What is Claude Sonnet 4?
Claude Sonnet 4 is Anthropic's mid-tier model released in May 2025, delivering strong results in reasoning, coding, multilingual tasks, and long-context handling. It is positioned between Claude Haiku (fastest) and Claude Opus (most capable) in Anthropic's model family.
Is Claude Sonnet 4 better than GPT-4?
Claude Sonnet 4 outperforms GPT-4 on several benchmarks including coding and instruction-following tasks. Independent comparisons show it performs competitively with GPT-4o while offering strengths in nuanced text processing and reduced hallucination.
Is Claude Sonnet 4 or 3.7 better?
Claude Sonnet 4 improves over 3.7 in reasoning, honesty, and image processing while maintaining similar speed and pricing. The upgrade includes better handling of ambiguous instructions and fewer unnecessary refusals on benign requests.
Is Claude Sonnet 4 free to use?
Claude Sonnet 4 is available for free with usage limits through claude.ai. Through the API, it costs $3 per million input tokens and $15 per million output tokens. It is also accessible through cloud platforms like AWS Bedrock and Google Vertex AI.
Is Claude better than GPT?
Claude and GPT models each have different strengths. Claude Sonnet 4 tends to produce more nuanced, less formulaic writing and is often preferred for tasks requiring careful instruction-following. GPT-4o offers stronger multimodal capabilities. The best choice depends on your specific use case and priorities.