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.
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.
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.
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 |
|---|---|---|---|---|---|---|---|
| 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 |
| gemma-2b-it | text generation | English | 8,192 | 2.5B | small | gemma | |
| gemma-4-26B-A4B-it | text to-text | Multilingual | 262,144 | 25.8B | small | apache-2.0 | |
| gemma-4-31B-it | text generation | Multilingual | 131,072 | 30.7B | small | apache-2.0 | |
| meta-llama | Llama-3.3-70B-Instruct | text generation | Multilingual | 99,000 | 70.6B | large | 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-M2.7 | 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 | 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 | 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 | text generation | Multilingual | 400,000 | 0 | large | openai |
| gemini-2.5-flash | text generation | Multilingual | 400,000 | 0 | large | openai | |
| gemini-3.7-flash | text generation | Multilingual | 400,000 | 0 | large | openai | |
| groq | 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 | text generation | Multilingual | 400,000 | 0 | large | openai |
| openai | 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 | 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 |
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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 where nuanced understanding of context matters.
Claude Sonnet 4 is Anthropic's flagship production model, released in May 2025 as part of the Claude 4 model family. It balances strong reasoning capability with practical latency and cost for real-world deployments.
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, making it a preferred choice for developer workflows.
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 with co-located inference for reduced latency.
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 provide alternative access points with their own pricing.
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, Claude Sonnet 4 is the stronger choice.
Claude and ChatGPT each have advantages depending on the task. Claude Sonnet 4 tends to excel on coding, writing, and instruction following, while ChatGPT (GPT-5) has broader tool integration with web search, image generation, and plugins.
