added new mod for glm4.7-flash-awq, solo model support.

README.md

@@ -146,7 +146,63 @@ For periodic maintenance, I recommend using a filter: `docker builder prune --fi
 
 ### 2026-01-29
 
-Added `-e` / `--env` parameter to `launch-cluster.sh` to pass environment variables to the container.
+#### New Parameters for launch-cluster.sh
+
+- Added **solo mode** to `launch-cluster.sh` to launch models on a single node. Just use `--solo` flag  or if you have only a single Spark, it will default to Solo mode if no other nodes are found.
+- Added `-e` / `--env` parameter to `launch-cluster.sh` to pass environment variables to the container.
+
+#### New Mod for GLM-4.7-Flash-AWQ
+
+Added a mod to prevent severe inference speed degradation when using cyankiwi/GLM-4.7-Flash-AWQ-4bit (and potentially other AWQ quants of this model).
+See (this post on NVIDIA forums)[https://forums.developer.nvidia.com/t/make-glm-4-7-flash-go-brrrrr/359111] for implementation details.
+
+To use the mod, first build the container with Transformers 5 support (`--pre-tf`) flag, e.g.:
+
+```bash
+./build-and-copy.sh -t vllm-node-tf5 --use-wheels --pre-tf -c
+```
+
+Drop `--use-wheels` if you experience an error during build (see the annoucement in the Quick Start section).
+
+Then, to run on a single node:
+
+```bash
+./launch-cluster.sh -t vllm-node-tf5 --solo \
+  --apply-mod mods/fix-glm-4.7-flash-AWQ \
+  exec vllm serve cyankiwi/GLM-4.7-Flash-AWQ-4bit \
+  --tool-call-parser glm47 \
+  --reasoning-parser glm45 \
+  --enable-auto-tool-choice \
+  --served-model-name glm-4.7-flash \
+  --max-model-len 202752 \
+  --max-num-batched-tokens 4096 \
+  --max-num-seqs 64 \
+  --host 0.0.0.0 --port 8888 \
+  --gpu-memory-utilization 0.7
+```
+
+To run on cluster:
+
+```bash
+./launch-cluster.sh -t vllm-node-tf5 \
+  --apply-mod mods/fix-glm-4.7-flash-AWQ \
+  exec vllm serve cyankiwi/GLM-4.7-Flash-AWQ-4bit \
+  --tool-call-parser glm47 \
+  --reasoning-parser glm45 \
+  --enable-auto-tool-choice \
+  --served-model-name glm-4.7-flash \
+  --max-model-len 202752 \
+  --max-num-batched-tokens 4096 \
+  --max-num-seqs 64 \
+  --host 0.0.0.0 --port 8888 \
+  --gpu-memory-utilization 0.7 \
+  --distributed-executor-backend ray \
+  --tensor-parallel-size 2
+```
+
+**NOTE**: vLLM implementation is suboptimal even with the patch. The model performance is still significantly slower than it should be for the model with this number of active parameters. Running in the cluster increases prompt processing performance, but not token generation. You can expect ~40 t/s generation speed in both single node and cluster.
+
+#### Experimental Optimized MXFP4 Build
 
 Added an experimental build option, optimized for DGX Spark and gpt-oss models by [Christopher Owen](https://github.com/christopherowen/spark-vllm-mxfp4-docker/blob/main/Dockerfile).
 
@@ -537,6 +593,7 @@ You can override the auto-detected values if needed:
 | `--apply-mod` | Apply mods/patches from specified directory. Can be used multiple times to apply multiple mods. |
 | `--nccl-debug` | NCCL debug level (e.g., INFO, WARN). Defaults to INFO if flag is present but value is omitted. |
 | `--check-config` | Check configuration and auto-detection without launching. |
+| `--solo` | Solo mode: skip autodetection, launch only on current node, do not launch Ray cluster |
 | `-d` | Run in daemon mode (detached). |
 
 ## 3\. Running the Container (Manual)

launch-cluster.sh

@@ -27,9 +27,12 @@ CLUSTER_WAS_RUNNING="false"
 MOD_PATHS=()
 MOD_TYPES=()
 
+ACTIONS_ARG=""
+SOLO_MODE="false"
+
 # Function to print usage
 usage() {
-    echo "Usage: $0 [-n <node_ips>] [-t <image_name>] [--name <container_name>] [--eth-if <if_name>] [--ib-if <if_name>] [--nccl-debug <level>] [--check-config] [-d] [action] [command]"
+    echo "Usage: $0 [-n <node_ips>] [-t <image_name>] [--name <container_name>] [--eth-if <if_name>] [--ib-if <if_name>] [--nccl-debug <level>] [--check-config] [--solo] [-d] [action] [command]"
     echo "  -n, --nodes     Comma-separated list of node IPs (Optional, auto-detected if omitted)"
     echo "  -t              Docker image name (Optional, default: $IMAGE_NAME)"
     echo "  --name          Container name (Optional, default: $DEFAULT_CONTAINER_NAME)"
@@ -39,6 +42,7 @@ usage() {
     echo "  --nccl-debug    NCCL debug level (Optional, one of: VERSION, WARN, INFO, TRACE). If no level is provided, defaults to INFO."
     echo "  --apply-mod     Path to directory or zip file containing run.sh to apply before launch (Can be specified multiple times)"
     echo "  --check-config  Check configuration and auto-detection without launching"
+    echo "  --solo          Solo mode: skip autodetection, launch only on current node, do not launch Ray cluster"
     echo "  -d              Daemon mode (only for 'start' action)"
     echo "  action          start | stop | status | exec (Default: start)"
     echo "  command         Command to run (only for 'exec' action)"
@@ -64,6 +68,7 @@ while [[ "$#" -gt 0 ]]; do
             fi
             ;;
         --check-config) CHECK_CONFIG="true" ;;
+        --solo) SOLO_MODE="true" ;;
         -d) DAEMON_MODE="true" ;;
         -h|--help) usage ;;
         start|stop|status) 
@@ -145,7 +150,20 @@ source "$(dirname "$0")/autodiscover.sh"
 
 # Perform auto-detection
 detect_interfaces || exit 1
+
+if [[ "$SOLO_MODE" == "true" ]]; then
+    if [[ -n "$NODES_ARG" ]]; then
+        echo "Error: --solo is incompatible with -n/--nodes."
+        exit 1
+    fi
+    # Solo mode: skip node detection, just get local IP
+    detect_local_ip || exit 1
+    NODES_ARG="$LOCAL_IP"
+    PEER_NODES=()
+    echo "Solo mode enabled. Skipping node detection."
+else
     detect_nodes || exit 1
+fi
 
 if [[ -z "$NODES_ARG" ]]; then
     echo "Error: Nodes argument (-n) is mandatory or could not be auto-detected."
@@ -174,6 +192,12 @@ if [ "$FOUND_HEAD" = false ]; then
     exit 1
 fi
 
+# Implicit Solo Mode Detection
+if [[ "$SOLO_MODE" == "false" && ${#PEER_NODES[@]} -eq 0 ]]; then
+    echo "Only local node detected/configured. Activating solo mode (no Ray cluster)."
+    SOLO_MODE="true"
+fi
+
 echo "Head Node: $HEAD_IP"
 echo "Worker Nodes: ${PEER_NODES[*]}"
 echo "Container Name: $CONTAINER_NAME"
@@ -413,11 +437,19 @@ start_cluster() {
     echo "Starting Head Node on $HEAD_IP..."
     
     local head_cmd_args=()
+    if [[ "$SOLO_MODE" == "true" ]]; then
+        if [[ ${#MOD_PATHS[@]} -gt 0 ]]; then
+             head_cmd_args=(bash -c "echo Waiting for mod application...; while [ ! -f /tmp/mod_done ]; do sleep 1; done; echo Mod applied, starting container...; exec sleep infinity")
+        else
+             head_cmd_args=(sleep infinity)
+        fi
+    else
         if [[ ${#MOD_PATHS[@]} -gt 0 ]]; then
             head_cmd_args=(bash -c "echo Waiting for mod application...; while [ ! -f /tmp/mod_done ]; do sleep 1; done; echo Mod applied, starting node...; exec ./run-cluster-node.sh --role head --host-ip $HEAD_IP --eth-if $ETH_IF --ib-if $IB_IF")
         else
             head_cmd_args=(./run-cluster-node.sh --role head --host-ip "$HEAD_IP" --eth-if "$ETH_IF" --ib-if "$IB_IF")
         fi
+    fi
 
     docker run -d --privileged --gpus all --rm \
         --ipc=host --network host \
@@ -461,7 +493,13 @@ start_cluster() {
         done
     fi
 
+    if [[ "$SOLO_MODE" == "false" ]]; then
         wait_for_cluster
+    else
+        echo "Solo mode active: Skipping Ray cluster readiness check."
+        # Give container a moment to start up
+        sleep 2
+    fi
 }
 
 # Wait for Cluster Readiness

mods/fix-glm-4.7-flash-AWQ/glm47_flash.patch

@@ -0,0 +1,13 @@
+--- a/usr/local/lib/python3.12/dist-packages/vllm/v1/attention/backends/mla/triton_mla.py
++++ b/usr/local/lib/python3.12/dist-packages/vllm/v1/attention/backends/mla/triton_mla.py
+@@ -135,7 +135,9 @@
+         lse = torch.zeros(B, q_num_heads, dtype=q.dtype, device=q.device)
+
+         # For batch invariance, use only 1 split to ensure deterministic reduction
+-        num_kv_splits = 1 if vllm_is_batch_invariant() else 4
++        # Dynamic splits: ~1.5K tokens per split, clamped to [32, 128]
++        max_seq_len = int(attn_metadata.decode.seq_lens.max().item())
++        num_kv_splits = 1 if vllm_is_batch_invariant() else max(32, min(128, max_seq_len // 1500))
+
+         # TODO(lucas) Allocate ahead of time
+         attn_logits = torch.empty(

mods/fix-glm-4.7-flash-AWQ/run.sh

@@ -0,0 +1,3 @@
+#!/bin/bash
+set -e
+patch -p1 -d / < glm47_flash.patch