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🏆 The Overall Best Performing Open Source 7B Model 🏆 🤖 Outperforms ChatGPT (March) and Grok-1 🤖 🚀 15 -point improvement in Coding over OpenChat-3.5🚀 New Features 💡 2 Modes: Coding + Generalist, Mathematical Reasoning 💡 🧑‍⚖️ Experimental support for Evaluator and Feedback capabilities 🧑‍⚖️ To use this model, we highly recommend installing the OpenChat package by following the installation guide in our repository and using the OpenChat OpenAI-compatible API server by running the serving command from the table below. The server is optimized for high-throughput deployment using vLLM and can run on a consumer GPU with 24GB RAM. To enable tensor parallelism, append `--tensor-parallel-size N` to the serving command. Once started, the server listens at `localhost:18888` for requests and is compatible with the OpenAI ChatCompletion API specifications. Please refer to the example request below for reference. Additionally, you can use the OpenChat Web UI for a user-friendly experience.

Text generation
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
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🏆 The Overall Best Performing Open Source 7B Model 🏆 🤖 Outperforms ChatGPT (March) and Grok-1 🤖 🚀 15 -point improvement in Coding over OpenChat-3.5🚀 New Features 💡 2 Modes: Coding + Generalist, Mathematical Reasoning 💡 🧑‍⚖️ Experimental support for Evaluator and Feedback capabilities 🧑‍⚖️ 1. Usage 2. Benchmarks 3. Limitations 4. License 5. Dataset Details 6. Citation 7. Acknowledgements To use this model, we highly recommend installing the OpenChat package by following the installation guide in our repository and using the OpenChat OpenAI-compatible API server by running the serving command from the table below. The server is optimized for high-throughput deployment using vLLM and can run on a consumer GPU with 24GB RAM. To enable tensor parallelism, append `--tensor-parallel-size N` to the serving command.

Text generation
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

🏆 The Overall Best Performing Open-source 8B Model 🏆 🚀 Outperforms Llama-3-8B-Instruct and open-source finetunes/merges 🚀 To use this model, we highly recommend installing the OpenChat package by following the installation guide in our repository and using the OpenChat OpenAI-compatible API server by running the serving command from the table below. The server is optimized for high-throughput deployment using vLLM and can run on a consumer GPU with 24GB RAM. To enable tensor parallelism, append `--tensor-parallel-size N` to the serving command. Once started, the server listens at `localhost:18888` for requests and is compatible with the OpenAI ChatCompletion API specifications. Please refer to the example request below for reference. Additionally, you can use the OpenChat Web UI for a user-friendly experience.

Text generation
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
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1 M = 1 million tokens · USD
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How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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