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Qwen2.5-7B-Instruct-1M-GGUF

lmstudio-community

*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-7B-Instruct-1M **GGUF quantization:** provided by bartowski based on `llama.cpp` release b4546 Significantly improved performance in handling long-context tasks while maintaining its capability in short tasks.

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Qwen2.5-7B-Instruct-GGUF

lmstudio-community

*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-7B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b3772 Long context: Support for 128k tokens with yarn rope settings and 8k token generation

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-1.5B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b3772 Dataset improvements: featuring 5.5 trillion tokens to improve generstion, reasoning, and bug fixing.

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-14B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b4014 Up to 5.5 trillion training tokens including source code, text-code grounding, and synthetic data

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: Qwen2.5-Coder-14B-Instruct **MLX quantizations:** provided by bartowski from mlx-examples Up to 5.5 trillion training tokens including source code, text-code grounding, and synthetic data

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: Qwen2.5-Coder-14B-Instruct **MLX quantizations:** provided by bartowski from mlx-examples Up to 5.5 trillion training tokens including source code, text-code grounding, and synthetic data

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Qwen2.5-Coder-32B-GGUF

lmstudio-community

*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-32B **GGUF quantization:** provided by bartowski based on `llama.cpp` release b4058 This is a BASE model, and as such should be used for completion and generation, not chatting or instruct

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-32B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b4014 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: Qwen2.5-Coder-32B-Instruct **MLX quantizations:** provided by bartowski from mlx-examples Up to 5.5 trillion training tokens including source code, text-code grounding, and synthetic data

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: Qwen2.5-Coder-32B-Instruct **MLX quantizations:** provided by bartowski from mlx-examples Up to 5.5 trillion training tokens including source code, text-code grounding, and synthetic data

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-3B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b4014 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: Qwen2.5-Coder-3B-Instruct **MLX quantizations:** provided by bartowski from mlx-examples LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.

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*👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. **Model creator:** Qwen **Original model**: Qwen2.5-Coder-7B-Instruct **GGUF quantization:** provided by bartowski based on `llama.cpp` release b3772 Dataset improvements: featuring 5.5 trillion tokens to improve generstion, reasoning, and bug fixing.

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Cost analysis

Adjust monthly token usage to compare estimated API costs.

1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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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.

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

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

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