about
The first GPT-4 variant to support 128K tokens of context, GPT-4 Turbo shipped at 3x lower input pricing than standard GPT-4 while adding JSON mode, parallel function calling, and reproducible outputs via a seed parameter. Independent testing showed recall degrading past roughly 73K tokens, with performance matching base GPT-4 reliably up to 64K.
Licenseopenai
Context window(in thousands)128,000
Use cases for gpt-4-turbo-preview
- Full-codebase analysis: The 128K context window allows ingestion of entire repositories or large codebases in a single prompt for architecture review, dependency mapping, and refactoring.
- Deterministic output pipelines: The seed parameter enables reproducible generation, making it suited for automated testing, regression detection, and audit-ready content workflows.
- Multi-tool orchestration: Parallel function calling executes multiple API queries simultaneously within a single turn, reducing round-trip latency in agentic pipelines.
Quality
Arena Elo1324
MMLUN/A
MT BenchN/A
GPT-4 Turbo scores 86.5% on MMLU (5-shot), essentially matching the standard GPT-4 (86.4%) on the same sheet while expanding the context window to 128K tokens. Independent testing shows recall degrading past roughly 73K tokens, but at 64K context and below it maintains the same quality profile that made GPT-4 the reference benchmark.
pricing
Running GPT-4 Turbo through Telnyx Inference costs $10.00 per million input tokens and $30.00 per million output tokens. Analyzing 1,000,000 documents at 2,000 tokens each would cost approximately $40,000, a 3x reduction from standard GPT-4 ($180,000 for the same workload on GPT-4 32k).
What's Twitter saying?
- Developers praise GPT-4 Turbo as a major upgrade over GPT-4, with a larger context window, better instruction following, and strong performance in coding and blogging.
- Reviewers note its faster, cheaper operation compared to standard GPT-4, though preview versions show coding quality issues and output limits like 4,096 tokens.
- Benchmarks highlight inferiority to GPT-4o in latency, throughput (20 tokens/sec), precision, and multimodal tasks, per tech comparisons.
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 GPT-4 Turbo Preview?
GPT-4 Turbo Preview is an early-access variant of OpenAI's GPT-4 Turbo model with a 128K context window, JSON mode, and improved instruction following. It is available as the 0125 and 1106 snapshots through the API.
What's the difference between GPT-4 and GPT-4 Turbo?
GPT-4 Turbo expanded the context window from 8K/32K to 128K tokens while reducing API pricing by roughly 3x. It also added JSON mode and improved function calling that were not available in the original GPT-4.
How much is GPT-4 Turbo Preview?
GPT-4 Turbo Preview is priced at $10 per million input tokens and $30 per million output tokens, approximately one-third the cost of the original GPT-4. Newer models like GPT-4o offer even better pricing.
How can I access GPT-4 Turbo?
GPT-4 Turbo is accessible through the OpenAI API using model IDs like gpt-4-turbo-preview. It is also available through inference providers that offer hosted GPT-4 access.
Is GPT-4 Turbo free?
GPT-4 Turbo is not free through the API. It may be accessible in ChatGPT Plus with usage limits. For production use, hosted inference platforms offer access with usage-based pricing.
Why is GPT-4 Turbo cheaper than GPT-4?
OpenAI achieved lower pricing through architectural optimizations and a larger training dataset with a more recent knowledge cutoff (April 2024). The Turbo variant processes tokens more efficiently while maintaining comparable output quality.
What is GPT-4 Turbo good for?
GPT-4 Turbo excels at long-document analysis, code generation, and structured output tasks thanks to its 128K context window and JSON mode. For voice AI and real-time applications, its balance of capability and cost makes it a practical production choice.