Best Open-Source Chat Models Under 10B Parameters — 2024 Comparison
Comprehensive benchmark and comparison of sub-10B parameter open-source language models for dialogue tasks and real-world applications.
2026 update note
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Editorial note for 2026. This does not replace the historical article below.
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Best Open-Source Chat Models Under 10B Parameters — 2024 Benchmark
Methodology
We benchmarked Mistral-7B, Qwen-7B, Llama-2-7B, and Gemma-7B across MT-Bench (multi-turn), HumanEval (code), MMLU (knowledge), and GSM8K (math).
Results
| Model | MT-Bench | HumanEval | MMLU | GSM8K |
|---|---|---|---|---|
| Mistral-7B-Instruct | 6.84 | 30.5% | 62.5% | 48.2% |
| Qwen-7B-Chat | 7.12 | 28.6% | 58.7% | 52.1% |
| Llama-2-7B-Chat | 6.27 | 18.3% | 54.8% | 36.7% |
Analysis
Mistral-7B delivers the optimal balance of dialogue quality and inference efficiency. Qwen-7B leads in mathematical reasoning. For code generation tasks, DeepSeek-Coder-6.7B outperforms all general-purpose models in its class.
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