Cohere 新 30B 模型专攻智能体编程，比 Gemma 4 强
Cohere 推出了一款新的轻量级 30B 开源模型，基于 Command A+ 的并行 Transformer 架构，层数几乎翻倍。该模型专为智能体编程任务优化，在 Terminal-Bench 和 SWE-Bench 等基准测试中表现优于 Gemma 4。在 Terminal-Bench 中，模型需使用终端、检查环境、运行命令并读取输出；在 SWE-Bench 中，模型需处理真实 GitHub 软件问题，理解仓库、定位文件、生成补丁并通过测试。在 SciCode 和 LiveCodeBench 等传统代码基准上，模型也具备竞争力，但整体性能略低于 Qwen3.6。
Cool new open-weight model by Cohere: a new lightw…
Cool new open-weight model by Cohere: a new lightweight 30B open-weight model for agentic coding tasks.
This one builds on Command A+ using the parallel transformer design. Interestingly, even though it's almost half as big, it almost doubles the number of layers.
Also, they say that it's been specifically developed for agentic coding, not just coding. I.e., the evaluation is inside a workflow, not just on a single prompt-to-code-answer task.
For Terminal-Bench, the model has to use a terminal, inspect the environment, run commands, read outputs, etc.
For SWE-Bench the model works on real GitHub-style software issues where it has to understand the repository, find relevant files, make a patch, pass tests, etc.
SciCode and LiveCodeBench are more traditional because they mostly test whether the model can produce correct code for a specified problem. Sure, this still requires reasoning, but it's more like “Implement a numerical routine to compute a scientific quantity from given equations and inputs.” which doesn't require any interaction with the environment, existing files, tests, etc.
The focus on the agentic code benchmarks is probably why it's far ahead of Gemma 4 on those.
Overall, it's pretty competitive although not quite Qwen3.6-level performance.