Specifications
Context Window
128K tokens
Input Price/1M
$10.00
Output Price/1M
$30.00
Parameters
—
Max Output
4K tokens
Benchmarks
GPT-4 Turbo Preview results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 29.1 | 100.0 | Artificial Analysis official API |
| AA Coding Index | 21.5 | 100.0 | Artificial Analysis official API |
Math
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 73.7 | 100.0 | Artificial Analysis official API |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 69.4 | 100.0 | Artificial Analysis official API |
Information
- Release date
- January 25, 2024
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: GPT-4 Turbo Preview
What is GPT-4 Turbo Preview?
GPT-4 Turbo Preview is an AI model developed by OpenAI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via OpenAI's cloud API. With a context window of 128K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
GPT-4 Turbo Preview is usage-based, priced at $10/1M input tokens and $30/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The premium pricing reflects the model's frontier capabilities, recommended for complex reasoning, analysis, and generation tasks where quality takes priority over cost.
Benchmarks & Performance
GPT-4 Turbo Preview was evaluated on 5 different benchmarks, covering categories like Coding, Math, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
GPT-4 Turbo Preview is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, GPT-4 Turbo Preview competes directly with similarly capable models. Key competitors include Claude (Anthropic), Gemini (Google), and open source models like Llama (Meta) and Qwen (Alibaba). The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is GPT-4 Turbo Preview?
GPT-4 Turbo Preview is an AI model developed by OpenAI. It is a language model (LLM).
How much does GPT-4 Turbo Preview cost?
GPT-4 Turbo Preview costs $10/1M input tokens and $30/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does GPT-4 Turbo Preview compare with other models?
In available benchmarks, GPT-4 Turbo Preview scored: LiveCodeBench: 29.1/100, AA Coding Index: 21.5/100, MATH-500: 73.7/100. See the full table above for a detailed comparison.
Is GPT-4 Turbo Preview open source?
No, GPT-4 Turbo Preview is a proprietary model from OpenAI. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is GPT-4 Turbo Preview best for?
GPT-4 Turbo Preview excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →