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> [!NOTE] > **Qwopus3.8-27B-Flash-V2** is a renewed post-training release of Qwopus3.8-27B-Flash, whose foundation is Qwen3.8-27B. > [!TIP] > **Revised Rewards and Reinforcement Learning · Improved Python Formatting** Qwopus3.8-27B-Flash-V2 is a renewed post-training release of Qwopus3.8-27B-Flash, which itself is built on Qwen3.8-27B. The goal remains the same: preserve enough capability for demanding work while reducing ineffective reasoning and making long-running agent workloads more practical.

Code generationOpen weights
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Kimi K2.7 Code

月之暗面 · Kimi

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

Code generationOpen weights
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$0.6 / M input tokensOpenRouter · moonshotai/kimi-k2.7-code
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Codestral 2508

Mistral AI

Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. Blog Post

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$0.3 / M input tokensOpenRouter · mistralai/codestral-2508
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⚡ Each donation = another big MoE quantized I host 30+ free APEX MoE quantizations as independent research. My only local hardware is an NVIDIA DGX Spark (122 GB unified memory), enough for ~30-50B-class MoEs, but bigger ones (200B+) require rented compute on H100/H200/Blackwell, typically $20-100 per quant. If APEX quants are useful to you, your support directly funds those bigger runs. 🎉 Patreon (Monthly)  |  ☕ Buy Me a Coffee  |  ⭐ GitHub Sponsors **APEX (Adaptive Precision for EXpert Models)** quantizations of Kwaipilot/KAT-Coder-V2.5-Dev — Kwaipilot's Mixture-of-Experts model for agentic coding.

Code generationOpen weights
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⚡ Each donation = another big MoE quantized I host 30+ free APEX MoE quantizations as independent research. My only local hardware is an NVIDIA DGX Spark (122 GB unified memory), enough for ~30-50B-class MoEs, but bigger ones (200B+) require rented compute on H100/H200/Blackwell, typically $20-100 per quant. If APEX quants are useful to you, your support directly funds those bigger runs. 🎉 Patreon (Monthly)  |  ☕ Buy Me a Coffee  |  ⭐ GitHub Sponsors **APEX (Adaptive Precision for EXpert Models)** quantizations of poolside/Laguna-XS-2.1 — poolside's Laguna XS.2 Mixture-of-Experts model for coding and agentic software engineering.

Code generationOpen weights
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GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

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$1.25 / M input tokensOpenRouter · openai/gpt-5.1-codex
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GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...

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$1.25 / M input tokensOpenRouter · openai/gpt-5.1-codex-max
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GPT-5.2-Codex在编码性能、网络安全能力和长周期任务处理上均实现突破。OpenAI特别强调GPT-5.2-Codex在网络安全方面的显著提升

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$1.75 / M input tokensOpenRouter · openai/gpt-5.2-codex
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GPT-5.3-Codex通过性能提升、功能泛化和安全性升级,重新定义了AI在编程及泛生产力领域的角色

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$1.75 / M input tokensOpenRouter · openai/gpt-5.3-codex
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GPT-5.3-Codex通过性能提升、功能泛化和安全性升级,重新定义了AI在编程及泛生产力领域的角色

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GPT-5.3-Codex通过性能提升、功能泛化和安全性升级,重新定义了AI在编程及泛生产力领域的角色

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GPT-5.3-Codex通过性能提升、功能泛化和安全性升级,重新定义了AI在编程及泛生产力领域的角色

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GPT-5-Codex 是 GPT-5 的一个版本,针对 Codex 中的代理编码进行了优化。与其前身 codex-1 一样,该模型在各种环境中使用强化学习对真实世界的编码任务进行训练,以生成与人类风格和公关偏好密切相关的代码,精确遵守指令,并迭代运行测试,直到获得通过的结果。

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GPT-5-Codex 是 GPT-5 的一个版本,针对 Codex 中的代理编码进行了优化。与其前身 codex-1 一样,该模型在各种环境中使用强化学习对真实世界的编码任务进行训练,以生成与人类风格和公关偏好密切相关的代码,精确遵守指令,并迭代运行测试,直到获得通过的结果。

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GPT-5-Codex 是 GPT-5 的一个版本,针对 Codex 中的代理编码进行了优化。与其前身 codex-1 一样,该模型在各种环境中使用强化学习对真实世界的编码任务进行训练,以生成与人类风格和公关偏好密切相关的代码,精确遵守指令,并迭代运行测试,直到获得通过的结果。

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GPT-5-Codex 是 GPT-5 的一个版本,针对 Codex 中的代理编码进行了优化。与其前身 codex-1 一样,该模型在各种环境中使用强化学习对真实世界的编码任务进行训练,以生成与人类风格和公关偏好密切相关的代码,精确遵守指令,并迭代运行测试,直到获得通过的结果。

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The Pareto Router maintains a tiered shortlist of strong coding models, ranked by Artificial Analysis coding percentiles. Set min_coding_score between 0 and 1 on the pareto-router plugin to control how...

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