A plan for a big model: experts spread, any number of nodes, memory said
A mixture-of-experts model on more than one card is served with vLLM's --enable-expert-parallel; config.json's experts are read by any of their names, and a model that also reads pictures is sized by its text_config. Tensor parallelism past the KV heads is allowed when it is a multiple of them (Qwen3-235B, four KV heads, runs on eight cards), which the plan had refused. Several nodes are offered in any number, not only powers of two. Each way says what it needs of a card, part by part, and of all its cards; the serve form checks a context longer than planned still fits. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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@@ -10516,6 +10516,20 @@
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"bits_per_weight": {
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"type": "number",
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"description": "BitsPerWeight is the artifact's precision, 0 when unknown."
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},
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"weights_gb": {
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"type": "number",
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"description": "What NeedGB is made of, a card's share (or, on the CPU, the node's RAM): the weights, the context's KV cache, and the engine's own."
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},
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"context_gb": {
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"type": "number"
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},
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"engine_gb": {
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"type": "number"
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},
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"expert_parallel": {
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"type": "boolean",
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"description": "ExpertParallel spreads a mixture-of-experts model's experts over the cards, whole, rather than slicing each across them: vLLM's --enable-expert-parallel, for a model of experts on more than one card."
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}
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}
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},
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@@ -10620,6 +10634,11 @@
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"context": {
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"type": "integer"
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},
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"kv_bytes_per_token": {
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"type": "integer",
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"format": "int64",
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"description": "KVBytesPerToken is one token of context, the whole model: what an option needs for another context is worked out from it. 0 is unknown."
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},
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"gated": {
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"type": "boolean"
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},
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