about
The original March 2023 launch snapshot of GPT-4 shipped without function calling or the system message improvements that arrived in the 0613 update. A Stanford/Berkeley study later found that this snapshot scored 97.6% on prime number identification tasks where the 0613 version dropped to 2.4%, making it one of the most cited examples of capability regression between model snapshots.
Licenseopenai
Context window(in thousands)128000
Use cases for GPT-4 0314
- Reproducible baseline evaluation: As a frozen March 2023 checkpoint with no post-release updates, it serves as a stable reference point for benchmarking newer models and measuring capability progression.
- Concise analytical output: Known for producing shorter, more direct responses than later GPT-4 snapshots, it suits applications where brevity and precision are preferred over verbose explanation.
- Historical reasoning comparison: Research teams use this pinned snapshot to study capability changes between GPT-4 versions, including the documented regression on certain reasoning tasks in later snapshots.
Quality
Arena Elo1186
MMLU86.4
MT Bench8.96
GPT-4 0314 shares the 86.4% MMLU (5-shot) and 8.99 MT-Bench scores of the GPT-4 family at launch. As the original March 2023 checkpoint, it predates function calling and improved system message adherence introduced in the 0613 snapshot on the same sheet. A notable Stanford/Berkeley study found its performance on certain reasoning tasks diverged significantly from later snapshots, highlighting the instability of capability between GPT-4 versions.
pricing
The cost of utilizing this model with Telnyx Inference is $0.0010 per 1,000 tokens. For instance, analyzing 1,000,000 customer chats, assuming each chat is 1,000 tokens long, would cost $1,000.
What's Twitter saying?
- Developers and tech commentators praised GPT-4's March 2023 release for markedly improved performance in reasoning, retention, coding, and multimodal capabilities like image-to-code, outperforming GPT-3.5 on benchmarks.
- Some expressed concerns over safety issues, including early base model vulnerabilities like assassination suggestions and erratic Bing Chat behaviors, prompting calls for a six-month pause on stronger LLMs from figures like Elon Musk.
- Critics like Hugging Face researchers called it a "dead end" for science due to its closed nature, limiting community building, while later Hacker News threads noted perceived quality drops from added restrictions.
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 |
| 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 0314?
GPT-4 0314 is the original March 2023 snapshot of OpenAI's GPT-4 model with an 8,192-token context window. It was the first publicly available version of GPT-4 and was recognized for concise, high-quality output before later snapshots introduced additional capabilities.
What is the best version of GPT-4?
For current use, GPT-4o and GPT-4.1 are considered the best versions, offering stronger performance at lower prices. Among the original GPT-4 series, the 0314 snapshot was favored by many users for its concise output style before it was deprecated.
Is GPT-4 discontinued?
The original GPT-4 snapshots including 0314 have been deprecated by OpenAI. Users are directed to migrate to GPT-4o or GPT-4.1, which provide improved performance, larger context windows, and lower pricing.
Is GPT-4.1 cheaper than GPT-4o?
GPT-4.1 offers a 1M token context window and improved coding performance at competitive pricing. For detailed cost comparisons between GPT-4.1 and GPT-4o, OpenAI's pricing documentation provides current rates, with GPT-4.1 generally offering better value for coding and long-context tasks.
What is better, GPT-4.1 or GPT-4o?
GPT-4.1 outperforms GPT-4o on coding benchmarks and instruction-following with a larger 1M token context window. GPT-4o remains strong for multimodal tasks involving vision and audio processing. The choice depends on whether your primary use case is code-heavy or multimodal.