Ideal für: Coding
Ranked on SWE-Bench, HumanEval, and dollars-per-1M output tokens. Balanced for autonomous and assistive coding workflows.
Aktualisiert April 2026. Top 3 diesen Monat: GPT-4o (2024-11-20), Claude Sonnet 4.5, GPT-5 Codex.
Podium
So werten wir
Choosing an LLM for coding comes down to three things: how well it turns specifications into working code, how well it reasons about large repositories, and how much it will cost once you wire it into CI or an agent loop. We weight SWE-Bench heaviest because it best predicts real-world coding-agent success, followed by HumanEval for short-form correctness, and a price pillar so the recommendation survives contact with a finance review.
Our full methodology is published on the Methodik-Seite.
Säulen und Gewichte:
Full ranking
| Rang | Modell | Anbieter | Input $/1M | Output $/1M | Kontext |
|---|---|---|---|---|---|
| 1 | GPT-4o (2024-11-20) | OpenAI | $2.50 | $10.00 | 128,000 |
| 2 | Claude Sonnet 4.5 | Anthropic | $3.00 | $15.00 | 1,000,000 |
| 3 | GPT-5 Codex | OpenAI | $1.25 | $10.00 | 400,000 |
| 4 | Gemini 2.5 Pro | $1.25 | $10.00 | 1,048,576 | |
| 5 | Gemini 2.5 Pro Preview 06-05 | $1.25 | $10.00 | 1,048,576 | |
| 6 | GPT-5.1-Codex | OpenAI | $1.25 | $10.00 | 400,000 |
| 7 | o3 | OpenAI | $2.00 | $8.00 | 200,000 |
| 8 | Claude 3.7 Sonnet | Anthropic | $3.00 | $15.00 | 200,000 |
| 9 | Claude 3.7 Sonnet (thinking) | Anthropic | $3.00 | $15.00 | 200,000 |
| 10 | GPT-5 Mini | OpenAI | $0.25 | $2.00 | 400,000 |
Field notes
Prefer a model with a large context window if your repo is bigger than ~200 files.
Use batch pricing for CI / nightly refactor jobs; interactive IDE work stays on the standard price.
Check function-calling reliability before committing to an agentic flow.
FAQ
The questions teams ask before picking a model for coding.
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