deprecate LFM2-2.6B and LFM2-2.6B-Exp

lfm/help/deprecations.mdx

@@ -38,6 +38,22 @@
       <td><a href="https://huggingface.co/mlx-community/LFM2-1.2B-8bit">✓</a></td>
       <td><a href="https://huggingface.co/onnx-community/LFM2-1.2B-ONNX">✓</a></td>
     </tr>
+    <tr>
+      <td><a href="/lfm/models/lfm2-2.6b">LFM2-2.6B</a></td>
+      <td><a href="/lfm/models/lfm25-2.6b">LFM2.5-2.6B</a></td>
+      <td><a href="https://huggingface.co/LiquidAI/LFM2-2.6B">✓</a></td>
+      <td><a href="https://huggingface.co/LiquidAI/LFM2-2.6B-GGUF">✓</a></td>
+      <td><a href="https://huggingface.co/mlx-community/LFM2-2.6B-8bit">✓</a></td>
+      <td><a href="https://huggingface.co/onnx-community/LFM2-2.6B-ONNX">✓</a></td>
+    </tr>
+    <tr>
+      <td><a href="/lfm/models/lfm2-2.6b-exp">LFM2-2.6B-Exp</a></td>
+      <td><a href="/lfm/models/lfm25-2.6b">LFM2.5-2.6B</a></td>
+      <td><a href="https://huggingface.co/LiquidAI/LFM2-2.6B-Exp">✓</a></td>
+      <td><a href="https://huggingface.co/LiquidAI/LFM2-2.6B-Exp-GGUF">✓</a></td>
+      <td>✗</td>
+      <td>✗</td>
+    </tr>
     <tr>
       <td><a href="/lfm/models/lfm2-350m">LFM2-350M</a></td>
       <td><a href="/lfm/models/lfm25-350m">LFM2.5-350M</a></td>
@@ -71,7 +87,7 @@
       <td><a href="https://huggingface.co/mlx-community/LFM2-VL-450M-8bit">✓</a></td>
       <td><a href="https://huggingface.co/onnx-community/LFM2-VL-450M-ONNX">✓</a></td>
     </tr>
     <tr><td colSpan={6}><strong>Liquid Nanos</strong></td></tr>
     <tr>
       <td><a href="/lfm/models/lfm2-1.2b-extract">LFM2-1.2B-Extract</a></td>
       <td><a href="/lfm/models/lfm25-1.2b-instruct">LFM2.5-1.2B-Instruct</a></td>

lfm/models/complete-library.mdx

@@ -1,6 +1,6 @@
 ---
 title: "Liquid Foundation Models"
 description: "Liquid Foundation Models (LFMs) are a new class of multimodal architectures built for fast inference and on-device deployment. Browse all available models and formats here."
 ---
 
 <div className="capabilities">
@@ -38,7 +38,7 @@
   Interleaved audio/text models for TTS, ASR, and voice chat.
 </Card>
 
 <Card title="Liquid Nanos" icon="sparkles" href="/lfm/models/liquid-nanos">
   Task-specific models for extraction, summarization, RAG, and translation.
 </Card>
 
@@ -72,7 +72,7 @@
 
 - **GGUF** — Best for local CPU/GPU inference on any platform. Use with [llama.cpp](/deployment/on-device/llama-cpp), [LM Studio](/deployment/on-device/lm-studio), or [Ollama](/deployment/on-device/ollama). Append `-GGUF` to any model name.
 - **MLX** — Best for Mac users with Apple Silicon. Leverages unified memory for fast inference via [MLX](/deployment/on-device/mlx). Browse at [mlx-community](https://huggingface.co/mlx-community/collections?search=LFM).
 - **ONNX** — Best for production deployments and edge devices. Cross-platform with ONNX Runtime across CPUs, GPUs, and accelerators. Append `-ONNX` to any model name.
 
 ### Quantization
 
@@ -96,8 +96,6 @@
 | [LFM2.5-2.6B](/lfm/models/lfm25-2.6b) | LFM2.5 (Latest release) | [✓](https://huggingface.co/LiquidAI/LFM2.5-2.6B) | [✓](https://huggingface.co/LiquidAI/LFM2.5-2.6B-GGUF) | [✓](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX) | [✓](https://huggingface.co/LiquidAI/LFM2.5-2.6B-ONNX) | Yes (TRL) |
 | [LFM2.5-8B-A1B](/lfm/models/lfm25-8b-a1b) | LFM2.5 (Latest release) | [✓](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B) | [✓](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B-GGUF) | [✓](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B-MLX-8bit) | [✓](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B-ONNX) | Yes (TRL) |
 | [LFM2-24B-A2B](/lfm/models/lfm2-24b-a2b) | LFM2 | [✓](https://huggingface.co/LiquidAI/LFM2-24B-A2B) | [✓](https://huggingface.co/LiquidAI/LFM2-24B-A2B-GGUF) | [✓](https://huggingface.co/LiquidAI/LFM2-24B-A2B-MLX-8bit) | [✓](https://huggingface.co/LiquidAI/LFM2-24B-A2B-ONNX) | Yes (TRL) |
-| [LFM2-2.6B](/lfm/models/lfm2-2.6b) | LFM2 | [✓](https://huggingface.co/LiquidAI/LFM2-2.6B) | [✓](https://huggingface.co/LiquidAI/LFM2-2.6B-GGUF) | [✓](https://huggingface.co/mlx-community/LFM2-2.6B-8bit) | [✓](https://huggingface.co/onnx-community/LFM2-2.6B-ONNX) | Yes (TRL) |
-| [LFM2-2.6B-Exp](/lfm/models/lfm2-2.6b-exp) | LFM2 | [✓](https://huggingface.co/LiquidAI/LFM2-2.6B-Exp) | [✓](https://huggingface.co/LiquidAI/LFM2-2.6B-Exp-GGUF) | ✗ | ✗ | Yes (TRL) |
 | [LFM2-700M](/lfm/models/lfm2-700m) | LFM2 | [✓](https://huggingface.co/LiquidAI/LFM2-700M) | [✓](https://huggingface.co/LiquidAI/LFM2-700M-GGUF) | [✓](https://huggingface.co/mlx-community/LFM2-700M-8bit) | [✓](https://huggingface.co/onnx-community/LFM2-700M-ONNX) | Yes (TRL) |
 | **Vision Language Models** | | | | | | |
 | [LFM2.5-VL-3B](/lfm/models/lfm25-vl-3b) | LFM2.5 (Latest release) | [✓](https://huggingface.co/LiquidAI/LFM2.5-VL-3B) | [✓](https://huggingface.co/LiquidAI/LFM2.5-VL-3B-GGUF) | [✓](https://huggingface.co/LiquidAI/LFM2.5-VL-3B-MLX-8bit) | [✓](https://huggingface.co/LiquidAI/LFM2.5-VL-3B-ONNX) | Yes (TRL) |

lfm/models/lfm2-2.6b-exp.mdx

@@ -1,6 +1,6 @@
 ---
 title: "LFM2-2.6B-Exp"
-description: "RL-only post-trained 2.6B model with improved math and reasoning capabilities"
+description: "RL-only post-trained 2.6B model with improved math and reasoning capabilities (deprecated - use LFM2.5-2.6B instead)"
 ---
 
 import { TextTransformers } from "/snippets/quickstart/text-transformers.mdx";
@@ -10,6 +10,10 @@
 
 <a href="/lfm/models/text-models" className="back-button">← Back to Text Models</a>
 
+<Warning>
+This model is deprecated. Use [LFM2.5-2.6B](/lfm/models/lfm25-2.6b) for improved agentic capabilities, 128K context, and native tool calling.
+</Warning>
+
 LFM2-2.6B-Exp is an experimental checkpoint of LFM2-2.6B with RL-only post-training, delivering improved performance on math and reasoning benchmarks. Use this model when you need stronger analytical capabilities.
 
 <div style={{display: 'flex', gap: '0.5rem', margin: '0.5rem 0 1.5rem 0'}}>

lfm/models/lfm2-2.6b.mdx

@@ -1,6 +1,6 @@
 ---
 title: "LFM2-2.6B"
-description: "Highly capable 2.6B parameter model for deployment on most phones and laptops"
+description: "Highly capable 2.6B parameter model for deployment on most phones and laptops (deprecated - use LFM2.5-2.6B instead)"
 ---
 
 import { TextTransformers } from "/snippets/quickstart/text-transformers.mdx";
@@ -10,6 +10,10 @@
 
 <a href="/lfm/models/text-models" className="back-button">← Back to Text Models</a>
 
+<Warning>
+This model is deprecated. Use [LFM2.5-2.6B](/lfm/models/lfm25-2.6b) for improved agentic capabilities, 128K context, and native tool calling.
+</Warning>
+
 LFM2-2.6B is a versatile mid-sized model delivering strong performance across chat, reasoning, and tool-calling tasks. Optimized for deployment on consumer devices including phones and laptops.
 
 <div style={{display: 'flex', gap: '0.5rem', margin: '0.5rem 0 1.5rem 0'}}>

lfm/models/text-models.mdx

@@ -47,7 +47,7 @@
 <Card title="LFM2.5-1.2B-Base" href="/lfm/models/lfm25-1.2b-base">
   1.2B · <Badge shape="pill" color="orange">Pre-trained</Badge>
 
   Base model for finetuning or custom checkpoints.
 </Card>
 
 <Card title="LFM2.5-1.2B-JP" href="/lfm/models/lfm25-1.2b-jp">
@@ -59,13 +59,13 @@
 <Card title="LFM2.5-2.6B" href="/lfm/models/lfm25-2.6b">
   2.6B · <Badge shape="pill" color="purple">Agentic</Badge>
 
   Dense model trained for agentic workloads, with 128K context and native tool calling for on-device agents.
 </Card>
 
 <Card title="LFM2.5-8B-A1B" href="/lfm/models/lfm25-8b-a1b">
   8B · 1.5B active · <Badge shape="pill" color="blue">MoE</Badge>
 
   Mixture-of-experts reasoning model with 128K context for on-device tool calling and agentic tasks.
 </Card>
 
 <Card title="LFM2.5-350M" href="/lfm/models/lfm25-350m">
@@ -92,18 +92,6 @@
   Our largest model for laptops and single-GPU applications.
 </Card>
 
-<Card title="LFM2-2.6B" href="/lfm/models/lfm2-2.6b">
-  2.6B
-
-  Highly capable model for deployment on most phones and laptops.
-</Card>
-
-<Card title="LFM2-2.6B-Exp" href="/lfm/models/lfm2-2.6b-exp">
-  2.6B
-
-  RL-only post-trained checkpoint for improved math and reasoning.
-</Card>
-
 <Card title="LFM2-700M" href="/lfm/models/lfm2-700m">
   700M