models: lower qwen3.5 0.8b/2b/4b footprint, note the mmap scope in the docs

docs/docs/models/qwen.md

@@ -387,7 +387,7 @@ The `-r` option determines the image's height:
 - Image understanding adapts to image size. Image TTFT can range from under 1 second to ~200 seconds depending on resolution. Use lower-resolution images (720p or below) unless high resolution is required (e.g. OCR on small text).
 - Video understanding is not supported yet.
 - In server mode this model reuses the prompts it has already read (system prompt, tools, earlier turns), so agents such as Hermes wait for new text only. See [Prefix Cache (Prompt Reuse)](https://fastflowlm.com/docs/instructions/server/prefix_cache/).
-- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 485 MiB table. This saves about 0.5 GiB of RAM (private memory at 4k context: about 0.8 GiB before, 0.3 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model.
+- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 485 MiB table. This saves about 0.5 GiB of RAM (private memory at 4k context: about 0.8 GiB before, 0.3 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model. This applies to the Qwen3.5 0.8B, 2B and 4B only; the 9B and the other model families still keep their embedding tables in RAM.
 
 ---
 
@@ -440,7 +440,7 @@ The `-r` option determines the image's height:
 - Image understanding adapts to image size. Image TTFT can range from under 1 second to ~200 seconds depending on resolution. Use lower-resolution images (720p or below) unless high resolution is required (e.g. OCR on small text).
 - Video understanding is not supported yet.
 - In server mode this model reuses the prompts it has already read (system prompt, tools, earlier turns), so agents such as Hermes wait for new text only. See [Prefix Cache (Prompt Reuse)](https://fastflowlm.com/docs/instructions/server/prefix_cache/).
-- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 970 MiB table. This saves about 1 GiB of RAM (private memory at 4k context: about 1.2 GiB before, 0.3 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model.
+- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 970 MiB table. This saves about 1 GiB of RAM (private memory at 4k context: about 1.2 GiB before, 0.3 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model. This applies to the Qwen3.5 0.8B, 2B and 4B only; the 9B and the other model families still keep their embedding tables in RAM.
 
 ---
 
@@ -493,7 +493,7 @@ The `-r` option determines the image's height:
 - Image understanding adapts to image size. Image TTFT can range from under 1 second to ~200 seconds depending on resolution. Use lower-resolution images (720p or below) unless high resolution is required (e.g. OCR on small text).
 - Video understanding is not supported yet.
 - In server mode this model reuses the prompts it has already read (system prompt, tools, earlier turns), so agents such as Hermes wait for new text only. See [Prefix Cache (Prompt Reuse)](https://fastflowlm.com/docs/instructions/server/prefix_cache/).
-- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 1.2 GiB table. This saves about 1.2 GiB of RAM (private memory at 4k context: about 1.8 GiB before, 0.6 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model.
+- Host memory: the token embeddings are read straight from `model.q4nx` through a read-only memory map, one row per token, instead of being unpacked into a 1.2 GiB table. This saves about 1.2 GiB of RAM (private memory at 4k context: about 1.8 GiB before, 0.6 GiB now) with the same speed and the same output. Only the rows of tokens that were actually seen stay in memory, and the OS can drop them under memory pressure; if it does, a prompt full of new tokens takes about a second longer to start. On Windows, the loaded model's `model.q4nx` cannot be replaced or deleted, so stop the server before `flm remove` or `flm pull` of this model. This applies to the Qwen3.5 0.8B, 2B and 4B only; the 9B and the other model families still keep their embedding tables in RAM.
 
 ---
 

src/model_list.json

@@ -464,7 +464,7 @@
                     "vision",
                     "reasoning"
                 ],
-                "footprint": 1.3
+                "footprint": 0.9
             },
             "2b": {
                 "supported_platforms": ["aie2p"],
@@ -497,7 +497,7 @@
                     "reasoning",
                     "tool-calling"
                 ],
-                "footprint": 3.1
+                "footprint": 2.2
             },
             "4b": {
                 "supported_platforms": ["aie2p"],
@@ -530,7 +530,7 @@
                     "reasoning",
                     "tool-calling"
                 ],
-                "footprint": 5.0
+                "footprint": 3.9
             },
             "9b":{
                 "supported_platforms": ["aie2p"],