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@@ -1,6 +1,6 @@
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engine = "vllm"
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name = "MiniMax M3 MXFP8 (vLLM)"
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-docker_image = "aidendle94/sparkrun-vllm-ds4-gb10:production-v2"
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+docker_image = "vllm/vllm-openai:minimax-m3"
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model = "MiniMaxAI/MiniMax-M3-MXFP8"
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required_nodes = 4
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tensor_parallel_size = 4
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@@ -12,12 +12,14 @@ distributed_backend = "mp"
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# MSA sparse attention requires --block-size 128.
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# Text-only mode skips the vision encoder to save VRAM.
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-entrypoint = ["vllm", "serve"]
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+#entrypoint = ["vllm", "serve"]
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args = [
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"--block-size", "128",
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"--kv-cache-dtype", "fp8",
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"--gpu-memory-utilization", "0.85",
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+ "--load-format", "safetensors",
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+ "--enable-prefix-caching",
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"--tool-call-parser", "minimax_m3",
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"--reasoning-parser", "minimax_m3",
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"--enable-auto-tool-choice",
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@@ -28,5 +30,11 @@ args = [
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]
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[env]
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+# Force colored logs through Docker pipeline
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+VLLM_LOGGING_COLOR = "1"
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+
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# M3 supports thinking via chat_template_kwargs.thinking_mode
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# enabled / adaptive / disabled — pass per-request in extra_body
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+SAFETENSORS_FAST_GPU = "1"
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+VLLM_ALLOW_LONG_MAX_MODEL_LEN = "1"
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+VLLM_USE_B12X_MOE = "1"
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