# Evaluate Model: LLM Benchmark Summary (April 2026): GPT-5.4, Gemini 3.1, Claude 4.6, Llama 4
## What This Is
As of April 2026, there is no single best AI model for all tasks. Google's Gemini 3.1 Pro Preview leads in general knowledge and reasoning benchmarks, while Anthropic's Claude Opus 4.6 is the top performer for coding tasks, and Meta's Llama 4 offers an unprecedented 10 million token context window for processing large documents.
Source: https://ianlpaterson.com/blog/llm-benchmark-2026-38-actual-tasks-15-models-for-2-29/
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and current AI integrations
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
- Which AI models I currently use and for what purposes
Then ask me before proceeding:
1. Am I interested in evaluating this model for my project, or just want a summary of what it offers?
2. If I want to try it — which part of my current AI stack should it replace or complement?
## Source Access Note
The source URL (https://ianlpaterson.com/blog/llm-benchmark-2026-38-actual-tasks-15-models-for-2-29/) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is a **New AI Model** — a model release, update, or capability announcement.
- Analyze the best use cases for this model within my project and current AI stack
- Compare its strengths, pricing, and context window against whatever I currently use
- Give me a clear, convincing argument for why this model would (or would not) be a good fit for my project
- If I want to try it: update my API configuration (provider, model ID, any new parameters) to point to this model
- If it requires a new API key or provider signup, tell me exactly what to do
## Additional Context
- Scan the user's active project to identify its primary function (e.g., code generation, RAG pipeline, multi-language support, data analysis).
- Based on the project's function, compare its requirements against the benchmark data to recommend the optimal model: Claude Opus 4.6 for coding, Gemini 3.1 Pro Preview for expert reasoning, or Llama 4 for long-document processing.
- Offer to update the project's configuration to use the recommended model. First, check for an existing API key for the corresponding provider (OpenAI, Google, Anthropic) in the user's environment variables. If a key is found, modify the API client instantiation to point to the new model endpoint; otherwise, prompt the user to add the required key.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it