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+

+ See Unsloth Dynamic 2.0 GGUFs for our quantization benchmarks. +

+
+ + + + + + + + + +
+ +
+ +
+ +# Kimi-K2.6 + +![kimi k2.6](https://unsloth.ai/docs/~gitbook/image?url=https%3A%2F%2F3215535692-files.gitbook.io%2F%7E%2Ffiles%2Fv0%2Fb%2Fgitbook-x-prod.appspot.com%2Fo%2Fspaces%252FxhOjnexMCB3dmuQFQ2Zq%252Fuploads%252FdBDLDaRXybr9JMCs33bC%252Fkimibench.jpg%3Falt%3Dmedia%26token%3D040ea87d-09e8-452c-bfb2-4231305a20d2&width=768&dpr=3&quality=100&sign=fb360710&sv=2) + +Kimi K2.6 is an open-source, native multimodal agentic model that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration. + +### Key Features +- **Long-Horizon Coding**: K2.6 achieves significant improvements on complex, end-to-end coding tasks, generalizing robustly across programming languages (Rust, Go, Python) and domains spanning front-end, DevOps, and performance optimization. +- **Coding-Driven Design**: K2.6 is capable of transforming simple prompts and visual inputs into production-ready interfaces and lightweight full-stack workflows, generating structured layouts, interactive elements, and rich animations with deliberate aesthetic precision. +- **Elevated Agent Swarm**: Scaling horizontally to 300 sub-agents executing 4,000 coordinated steps, K2.6 can dynamically decompose tasks into parallel, domain-specialized subtasks, delivering end-to-end outputs from documents to websites to spreadsheets in a single autonomous run. +- **Proactive & Open Orchestration**: For autonomous tasks, K2.6 demonstrates strong performance in powering persistent, 24/7 background agents that proactively manage schedules, execute code, and orchestrate cross-platform operations without human oversight. + +## 2. Model Summary + +
+ + +| | | +|:---:|:---:| +| **Architecture** | Mixture-of-Experts (MoE) | +| **Total Parameters** | 1T | +| **Activated Parameters** | 32B | +| **Number of Layers** (Dense layer included) | 61 | +| **Number of Dense Layers** | 1 | +| **Attention Hidden Dimension** | 7168 | +| **MoE Hidden Dimension** (per Expert) | 2048 | +| **Number of Attention Heads** | 64 | +| **Number of Experts** | 384 | +| **Selected Experts per Token** | 8 | +| **Number of Shared Experts** | 1 | +| **Vocabulary Size** | 160K | +| **Context Length** | 256K | +| **Attention Mechanism** | MLA | +| **Activation Function** | SwiGLU | +| **Vision Encoder** | MoonViT | +| **Parameters of Vision Encoder** | 400M | +
+ +## 3. Evaluation Results + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
BenchmarkKimi K2.6GPT-5.4
(xhigh)		Claude Opus 4.6
(max effort)		Gemini 3.1 Pro
(thinking high)		Kimi K2.5
Agentic
HLE-Full
(w/ tools)		54.052.153.051.450.2
BrowseComp83.282.783.785.974.9
BrowseComp
(Agent Swarm)		86.378.4
DeepSearchQA
(f1-score)		92.578.691.381.989.0
DeepSearchQA
(accuracy)		83.063.780.660.277.1
WideSearch
(item-f1)		80.8---72.7
Toolathlon50.054.647.248.827.8
MCPMark55.962.5*56.7*55.9*29.5
Claw Eval (pass^3)62.360.370.457.852.3
Claw Eval (pass@3)80.978.482.482.975.4
APEX-Agents27.933.333.032.011.5
OSWorld-Verified73.175.072.7-63.3
Coding
Terminal-Bench 2.0
(Terminus-2)		66.765.4*65.468.550.8
SWE-Bench Pro58.657.753.454.250.7
SWE-Bench Multilingual76.7-77.876.9*73.0
SWE-Bench Verified80.2-80.880.676.8
SciCode52.256.651.958.948.7
OJBench (python)60.6-60.370.754.7
LiveCodeBench (v6)89.6-88.891.785.0
Reasoning & Knowledge
HLE-Full34.739.840.044.430.1
AIME 202696.499.296.798.395.8
HMMT 2026 (Feb)92.797.796.294.787.1
IMO-AnswerBench86.091.475.391.0*81.8
GPQA-Diamond90.592.891.394.387.6
Vision
MMMU-Pro79.481.273.983.0*78.5
MMMU-Pro (w/ python)80.182.177.385.3*77.7
CharXiv (RQ)80.482.8*69.180.2*77.5
CharXiv (RQ) (w/ python)86.790.0*84.789.9*78.7
MathVision87.492.0*71.2*89.8*84.2
MathVision (w/ python)93.296.1*84.6*95.7*85.0
BabyVision39.849.714.851.636.5
BabyVision (w/ python)68.580.2*38.4*68.3*40.5
V* (w/ python)96.998.4*86.4*96.9*86.9
+
+ +
+Footnotes + +1. **General Testing Details** + - We report results for Kimi K2.6 and Kimi K2.5 with thinking mode enabled, Claude Opus 4.6 with max effort, GPT-5.4 with xhigh reasoning effort, and Gemini 3.1 Pro with a high thinking level. + - Unless otherwise specified, all Kimi K2.6 experiments were conducted with temperature = 1.0, top-p = 1.0, and a context length of 262,144 tokens. + - Benchmarks without publicly available scores were re-evaluated under the same conditions used for Kimi K2.6 and are marked with an asterisk (`*`). Except where noted with an asterisk, all other results are cited from official reports. +2. **Reasoning Benchmarks** + - IMO-AnswerBench scores for GPT-5.4 and Claude 4.6 were obtained from [z.ai/blog/glm-5.1](https://z.ai/blog/glm-5.1). + - Humanity's Last Exam (HLE) and other reasoning tasks were evaluated with a maximum generation length of 98,304 tokens. By default, we report results on the HLE full set. For the text-only subset, Kimi K2.6 achieves 36.4% accuracy without tools and 55.5% with tools. +3. **Tool-Augmented / Agentic Tasks** + - Kimi K2.6 was equipped with search, code-interpreter, and web-browsing tools for HLE with tools, BrowseComp, DeepSearchQA, and WideSearch. + - For HLE-Full with tools, the maximum generation length is 262,144 tokens with a per-step limit of 49,152 tokens. We employ a simple context management strategy: once the context window exceeds the threshold, only the most recent round of tool-related messages is retained. + - For BrowseComp, we report scores obtained with context management using the same discard-all strategy as Kimi K2.5 and DeepSeek-V3.2. + - For DeepSearchQA, no context management was applied to Kimi K2.6 tests, and tasks exceeding the supported context length were directly counted as failed. Scores for Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro on DeepSearchQA are cited from the [Claude Opus 4.7 System Card](https://cdn.sanity.io/files/4zrzovbb/website/037f06850df7fbe871e206dad004c3db5fd50340.pdf). + - For WideSearch, we report results under the "hide tool result" context management setting. Once the context window exceeds the threshold, only the most recent round of tool-related messages is retained. + - The test system prompts are identical to those used in the [Kimi K2.5 technical report](https://arxiv.org/pdf/2602.02276). + - Claw Eval was conducted using version 1.1 with max-tokens-per-step = 16384. + - For APEX-Agents, we evaluate 452 tasks from the public 480-task release, as done by [Artificial Analysis](https://artificialanalysis.ai/evaluations/apex-agents-aa)(excluding Investment Banking Worlds 244 and 246, which have external runtime dependencies) +4. **Coding Tasks** + - Terminal-Bench 2.0 scores were obtained with the default agent framework (Terminus-2) and the provided JSON parser, operating in preserve thinking mode. + - For the SWE-Bench series of evaluations (including Verified, Multilingual, and Pro), we used an in-house evaluation framework adapted from SWE-agent. This framework includes a minimal set of tools—bash tool, createfile tool, insert tool, view tool, strreplace tool, and submit tool. + - All reported scores for coding tasks are averaged over 10 independent runs. +5. **Vision Benchmarks** + - Max-tokens = 98,304, averaged over three runs (avg@3). + - Settings with Python tool use max-tokens-per-step = 65,536 and max-steps = 50 for multi-step reasoning. + - MMMU-Pro follows the official protocol, preserving input order and prepending images. + +
+ + +## 4. Native INT4 Quantization +Kimi-K2.6 adopts the same native int4 quantization method as [Kimi-K2-Thinking](https://huggingface.co/moonshotai/Kimi-K2-Thinking#4-native-int4-quantization). + +## 5. Deployment + +> [!Note] +> You can access Kimi-K2.6's API on https://platform.moonshot.ai and we provide OpenAI/Anthropic-compatible API for you. To verify the deployment is correct, we also provide the [Kimi Vendor Verifier](https://kimi.com/blog/kimi-vendor-verifier.html). +Currently, Kimi-K2.6 is recommended to run on the following inference engines: +* vLLM +* SGLang +* KTransformers + +Kimi-K2.6 has the same architecture as Kimi-K2.5, and the deployment method can be directly reused. + +The version requirement for `transformers` is `>=4.57.1, <5.0.0`. + +Deployment examples can be found in the [Model Deployment Guide](docs/deploy_guidance.md). + + +--- +## 6. Model Usage + +The usage demos below demonstrate how to call our official API. + +For third-party APIs deployed with vLLM or SGLang, please note that: +> [!Note] +> - Chat with video content is an experimental feature and is only supported in our official API for now. +> +> - The recommended `temperature` will be `1.0` for Thinking mode and `0.6` for Instant mode. +> +> - The recommended `top_p` is `0.95`. +> +> - To use instant mode, you need to pass `{'chat_template_kwargs': {"thinking": False}}` in `extra_body`. + +### Chat Completion + +This is a simple chat completion script which shows how to call K2.6 API in Thinking and Instant modes. + +```python +import openai +import base64 +import requests +def simple_chat(client: openai.OpenAI, model_name: str): + messages = [ + {'role': 'system', 'content': 'You are Kimi, an AI assistant created by Moonshot AI.'}, + { + 'role': 'user', + 'content': [ + {'type': 'text', 'text': 'which one is bigger, 9.11 or 9.9? think carefully.'} + ], + }, + ] + response = client.chat.completions.create( + model=model_name, messages=messages, stream=False, max_tokens=4096 + ) + print('====== Below is reasoning content in Thinking Mode ======') + print(f'reasoning content: {response.choices[0].message.reasoning}') + print('====== Below is response in Thinking Mode ======') + print(f'response: {response.choices[0].message.content}') + + # To use instant mode, pass {"thinking" = {"type":"disabled"}} + response = client.chat.completions.create( + model=model_name, + messages=messages, + stream=False, + max_tokens=4096, + extra_body={'thinking': {'type': 'disabled'}}, # this is for official API + # extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang + ) + print('====== Below is response in Instant Mode ======') + print(f'response: {response.choices[0].message.content}') +``` + + +### Chat Completion with visual content + +K2.6 supports Image and Video input. + +The following example demonstrates how to call K2.6 API with image input: + +```python +import openai +import base64 +import requests + +def chat_with_image(client: openai.OpenAI, model_name: str): + url = 'https://huggingface.co/moonshotai/Kimi-K2.6/resolve/main/figures/kimi-logo.png' + image_base64 = base64.b64encode(requests.get(url).content).decode() + messages = [ + { + 'role': 'user', + 'content': [ + {'type': 'text', 'text': 'Describe this image in detail.'}, + { + 'type': 'image_url', + 'image_url': {'url': f'data:image/png;base64, {image_base64}'}, + }, + ], + } + ] + + response = client.chat.completions.create( + model=model_name, messages=messages, stream=False, max_tokens=8192 + ) + print('====== Below is reasoning content in Thinking Mode ======') + print(f'reasoning content: {response.choices[0].message.reasoning}') + print('====== Below is response in Thinking Mode ======') + print(f'response: {response.choices[0].message.content}') + + # Also support instant mode if you pass {"thinking" = {"type":"disabled"}} + response = client.chat.completions.create( + model=model_name, + messages=messages, + stream=False, + max_tokens=4096, + extra_body={'thinking': {'type': 'disabled'}}, # this is for official API + # extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang + ) + print('====== Below is response in Instant Mode ======') + print(f'response: {response.choices[0].message.content}') + + return response.choices[0].message.content +``` + +The following example demonstrates how to call K2.6 API with video input: + +```python +import openai +import base64 +import requests + +def chat_with_video(client: openai.OpenAI, model_name:str): + url = 'https://huggingface.co/moonshotai/Kimi-K2.6/resolve/main/figures/demo_video.mp4' + video_base64 = base64.b64encode(requests.get(url).content).decode() + messages = [ + { + "role": "user", + "content": [ + {"type": "text","text": "Describe the video in detail."}, + { + "type": "video_url", + "video_url": {"url": f"data:video/mp4;base64,{video_base64}"}, + }, + ], + } + ] + + response = client.chat.completions.create(model=model_name, messages=messages) + print('====== Below is reasoning content in Thinking Mode ======') + print(f'reasoning content: {response.choices[0].message.reasoning}') + print('====== Below is response in Thinking Mode ======') + print(f'response: {response.choices[0].message.content}') + + # Also support instant mode if pass {"thinking" = {"type":"disabled"}} + response = client.chat.completions.create( + model=model_name, + messages=messages, + stream=False, + max_tokens=4096, + extra_body={'thinking': {'type': 'disabled'}}, # this is for official API + # extra_body= {'chat_template_kwargs': {"thinking": False}} # this is for vLLM/SGLang + ) + print('====== Below is response in Instant Mode ======') + print(f'response: {response.choices[0].message.content}') + return response.choices[0].message.content +``` + +### Preserve Thinking +Kimi K2.6 supports `preserve_thinking` mode, which retains full reasoning content across multi-turn interactions and enhances performance in coding agent scenarios. + +This feature is disabled by default. The following example demonstrates how to call K2.6 API in `preserve_thinking` mode: + +```python +def chat_with_preserve_thinking(client: openai.OpenAI, model_name: str): + messages = [ + { + "role": "user", + "content": "Tell me three random numbers." + }, + { + "role": "assistant", + "reasoning_content": "I'll start by listing five numbers: 473, 921, 235, 215, 222, and I'll tell you the first three.", + "content": "473, 921, 235" + }, + { + "role": "user", + "content": "What are the other two numbers you have in mind?" + } + ] + + response = client.chat.completions.create( + model=model_name, + messages=messages, + stream=False, + max_tokens=4096, + extra_body={'thinking': {'type': 'enabled', 'keep': 'all'}}, # this is for official API + # extra_body={"chat_template_kwargs": {"thinking":True, "preserve_thinking": True}}, # this is for vLLM/SGLang + # We recommend enabling preserve_thinking only in think mode. + ) + # the assistant should mention 215 and 222 that appear in the prior reasoning content + print(f"response: {response.choices[0].message.reasoning}") + return response.choices[0].message.content + +``` + +### Interleaved Thinking and Multi-Step Tool Call + +K2.6 shares the same design of Interleaved Thinking and Multi-Step Tool Call as K2 Thinking. For usage example, please refer to the [K2 Thinking documentation](https://platform.moonshot.ai/docs/guide/use-kimi-k2-thinking-model#complete-example). + +### Coding Agent Framework + +Kimi K2.6 works best with Kimi Code CLI as its agent framework — give it a try at https://www.kimi.com/code. + + +--- + +## 7. License + +Both the code repository and the model weights are released under the [Modified MIT License](LICENSE). + +--- + +## 8. Third Party Notices + +See [THIRD PARTY NOTICES](THIRD_PARTY_NOTICES.md) + +--- + +## 9. Contact Us + +If you have any questions, please reach out at [support@moonshot.ai](mailto:support@moonshot.ai). \ No newline at end of file diff --git a/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00001-of-00008.gguf b/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00001-of-00008.gguf new file mode 100644 index 0000000000000000000000000000000000000000..e76db57dec5cd5dbc335dda591ea52392ba40123 --- /dev/null +++ b/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00001-of-00008.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6218da3cc528de6a7fb48f8c7fc4ad45f7dbeeba244b3df07c4c98b20b35121c +size 6913152 diff --git a/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00002-of-00008.gguf b/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00002-of-00008.gguf new file mode 100644 index 0000000000000000000000000000000000000000..005c9a2e7afc291dd9a0c1d0a93007a34fd631ad --- /dev/null +++ b/UD-Q2_K_XL/Kimi-K2.6-UD-Q2_K_XL-00002-of-00008.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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