Sync up the cookbook model lineup with the one from the docs (and add Kimi K2.5) (#371)

Author: nealwu

docs/model-lineup.mdx

@@ -7,45 +7,48 @@ The table below shows the models that are currently available in Tinker. We plan
 - In general, use MoE models, which are more cost effective than the dense models.
 - Use Base models only if you're doing research or are running the full post-training pipeline yourself
 - If you want to create a model that is good at a specific task or domain, use an existing post-trained model, and fine-tune it on your own data or environment.
-    - If you care about latency, use one of the Instruction models, which will start outputting tokens without a chain-of-thought.
-    - If you care about intelligence and robustness, use one of the Hybrid or Reasoning models, which can use long chain-of-thought.
+  - If you care about latency, use one of the Instruction models, which will start outputting tokens without a chain-of-thought.
+  - If you care about intelligence and robustness, use one of the Hybrid or Reasoning models, which can use long chain-of-thought.
 
 ## Full Listing
 
-| Model Name                                                                                      | Training Type | Architecture | Size      |
-| ----------------------------------------------------------------------------------------------- | ------------- | ------------ | --------- |
-| [Qwen/Qwen3-VL-235B-A22B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct)     | Vision        | MoE          | Large     |
-| [Qwen/Qwen3-VL-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct)         | Vision        | MoE          | Medium    |
-| [Qwen/Qwen3-235B-A22B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507) | Instruction   | MoE          | Large     |
-| [Qwen/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507)     | Instruction   | MoE          | Medium    |
-| [Qwen/Qwen3-30B-A3B](https://huggingface.co/Qwen/Qwen3-30B-A3B)                                 | Hybrid        | MoE          | Medium    |
-| [Qwen/Qwen3-30B-A3B-Base](https://huggingface.co/Qwen/Qwen3-30B-A3B-Base)                       | Base          | MoE          | Medium    |
-| [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B)                                         | Hybrid        | Dense        | Medium    |
-| [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)                                           | Hybrid        | Dense        | Small     |
-| [Qwen/Qwen3-8B-Base](https://huggingface.co/Qwen/Qwen3-8B-Base)                                 | Base          | Dense        | Small     |
-| [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)               | Instruction   | Dense        | Compact   |
-| [openai/gpt-oss-120b](https://huggingface.co/openai/gpt-oss-120b)                               | Reasoning     | MoE          | Medium    |
-| [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b)                                 | Reasoning     | MoE          | Small     |
-| [deepseek-ai/DeepSeek-V3.1](https://huggingface.co/deepseek-ai/DeepSeek-V3.1)                   | Hybrid        | MoE          | Large     |
-| [deepseek-ai/DeepSeek-V3.1-Base](https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base)         | Base          | MoE          | Large     |
-| [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B)                     | Base          | Dense        | Large     |
-| [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)   | Instruction   | Dense        | Large     |
-| [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B)                       | Base          | Dense        | Small     |
-| [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)     | Instruction   | Dense        | Small     |
-| [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B)                       | Base          | Dense        | Compact   |
-| [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B)                       | Base          | Dense        | Compact   |
-| [moonshotai/Kimi-K2-Thinking](https://huggingface.co/moonshotai/Kimi-K2-Thinking)               | Reasoning     | MoE          | Large     |
+| Model Name                                                                                      | Training Type      | Architecture | Size    |
+| ----------------------------------------------------------------------------------------------- | -------------      | ------------ | ------- |
+| [Qwen/Qwen3-VL-235B-A22B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct)     | Vision             | MoE          | Large   |
+| [Qwen/Qwen3-VL-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct)         | Vision             | MoE          | Medium  |
+| [Qwen/Qwen3-235B-A22B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507) | Instruction        | MoE          | Large   |
+| [Qwen/Qwen3-30B-A3B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507)     | Instruction        | MoE          | Medium  |
+| [Qwen/Qwen3-30B-A3B](https://huggingface.co/Qwen/Qwen3-30B-A3B)                                 | Hybrid             | MoE          | Medium  |
+| [Qwen/Qwen3-30B-A3B-Base](https://huggingface.co/Qwen/Qwen3-30B-A3B-Base)                       | Base               | MoE          | Medium  |
+| [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B)                                         | Hybrid             | Dense        | Medium  |
+| [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)                                           | Hybrid             | Dense        | Small   |
+| [Qwen/Qwen3-8B-Base](https://huggingface.co/Qwen/Qwen3-8B-Base)                                 | Base               | Dense        | Small   |
+| [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)               | Instruction        | Dense        | Compact |
+| [openai/gpt-oss-120b](https://huggingface.co/openai/gpt-oss-120b)                               | Reasoning          | MoE          | Medium  |
+| [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b)                                 | Reasoning          | MoE          | Small   |
+| [deepseek-ai/DeepSeek-V3.1](https://huggingface.co/deepseek-ai/DeepSeek-V3.1)                   | Hybrid             | MoE          | Large   |
+| [deepseek-ai/DeepSeek-V3.1-Base](https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base)         | Base               | MoE          | Large   |
+| [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B)                     | Base               | Dense        | Large   |
+| [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)   | Instruction        | Dense        | Large   |
+| [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B)                       | Base               | Dense        | Small   |
+| [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)     | Instruction        | Dense        | Small   |
+| [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B)                       | Base               | Dense        | Compact |
+| [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B)                       | Base               | Dense        | Compact |
+| [moonshotai/Kimi-K2-Thinking](https://huggingface.co/moonshotai/Kimi-K2-Thinking)               | Reasoning          | MoE          | Large   |
+| [moonshotai/Kimi-K2.5](https://huggingface.co/moonshotai/Kimi-K2.5)                             | Reasoning + Vision | MoE          | Large   |
 
 ## Legend
 
 ### Training Types
+
 - **Base**: Foundation models trained on raw text data, suitable for post-training research and custom fine-tuning.
 - **Instruction**: Models fine-tuned for following instructions and chat, optimized for fast inference.
 - **Reasoning**: Models that always use chain-of-thought reasoning before their "visible" output that responds to the prompt.
 - **Hybrid**: Models that can operate in both thinking and non-thinking modes, where the non-thinking mode requires using a special renderer or argument that disables chain-of-thought.
 - **Vision**: Vision-language models (VLMs) that can process images alongside text. See [Vision Inputs](/rendering#vision-inputs) for usage.
 
 ### Architecture
+
 - **Dense**: Standard transformer architecture with all parameters active
 - **MoE**: Mixture of Experts architecture with sparse activation