vh
7bdac80878
Prime, 2026-09-25: TEI serves embedding + reranking for esh-ml1 and the fleet from now on; fv-ml1 retires both once esh-ml1 is up. - stacks/embed-rerank: vLLM -> TEI 1.9.4 (89- Ada build), same ports 8001/8013, fail-closed truncation (--auto-truncate false; embed --max-batch-tokens 32768). - litellm: qwen3-embedding -> esh-ml1 only (hosted_vllm/, unchanged address); reranker -> huggingface/ provider at :8013 (hosted_vllm/ 422s on TEI's `texts` body). DB alias reranker-a3-bge-v2-m3 patched to the same target. - Verified via the gateway against the retiring fv-ml1 seats: embed cosine median 0.999927 (n=203); rerank top-1/top-3 29/30. - stacks/vllm: vllm-embed and vllm-rerank-a3 removed (containers retired on fv-ml1, GPU 1 freed ~6.1 GB); reward + coder unchanged. - Bake-off record moved to docs/pfi/embed-rerank-tei-vs-vllm-bakeoff.md; CLAUDE.md gains the TEI convention.
143 lines
6.0 KiB
Markdown
143 lines
6.0 KiB
Markdown
# fv-ml1 — GPU seat inventory and model lineage
|
||
|
||
<!-- GENERATED FILE — DO NOT EDIT BY HAND.
|
||
Regenerate: scripts/seat-inventory.py
|
||
Check drift: scripts/seat-inventory.py --check
|
||
Hand-edits are overwritten and, worse, drift silently while looking
|
||
authoritative — which is exactly the failure this file replaced. -->
|
||
|
||
**Generated 2026-09-14 17:45 UTC** by `scripts/seat-inventory.py`, read from the running
|
||
containers on `100.64.0.7` — `docker inspect`, `nvidia-smi`, each model's own
|
||
`config.json`, and the `.PROVENANCE.txt` siblings on `/tank`.
|
||
|
||
⚠ `.PROVENANCE.txt` lives *beside* the model directory, not inside it:
|
||
`/tank/aimodels/<model>.PROVENANCE.txt`. `ls <model>/` will not show it.
|
||
|
||
## Placement, KV cache and concurrency
|
||
|
||
| GPU | seat | VRAM | weights | KV tokens | ctx | concurrency | util |
|
||
|---|---|---|---|---|---|---|---|
|
||
| 0 | `vllm-cyberprev` | 46.0 GiB | 25.11 GiB | 359,372 | 262144 | **1.37×** | 0.40 |
|
||
| 0 | `vllm-gen-small` | 35.8 GiB | 23.98 GiB | 670,142 | 262144 | **2.56×** | 0.48 |
|
||
| 1 | `vllm-meromero-rp` | 43.0 GiB | 19.51 GiB | 320,774 | 262144 | **1.22×** | 0.52 |
|
||
| 1 | `vllm-erp-seat` | 27.1 GiB | 15.9 GiB | 534,649 | 262144 | **2.04×** | 0.24 |
|
||
| 1 | `vllm-reward` | 9.0 GiB | 4.41 GiB | 26,224 | 16384 | **1.60×** | 0.10 |
|
||
| 1 | `vllm-coder` | 6.1 GiB | 2.98 GiB | 77,056 | 16384 | **4.70×** | 0.055 |
|
||
| 1 | `vllm-embed` | 3.4 GiB | 1.12 GiB | 10,272 | 8192 | **1.25×** | 0.03 |
|
||
| 1 | `vllm-rerank-a3` | 2.1 GiB | 1.06 GiB | — | 8192 | — | 0.03 |
|
||
| 2 | `vllm-flash-next` | 93.1 GiB | 76.82 GiB | 344,155 | 262144 | **1.31×** | 0.96 |
|
||
|
||
**Concurrency** = KV tokens ÷ context: how many full-length requests fit at
|
||
once. Below ~1.0× the seat cannot hold even one conversation at its declared
|
||
context.
|
||
|
||
## Lineage and quantization
|
||
|
||
### `vllm-cyberprev` — GPU 0
|
||
|
||
- **serves:** `cyberprev-27b`, `cyberprev-27b-thinking`
|
||
- **model:** `/tank/aimodels/cyberprev-nvfp4-mixed-v2`
|
||
- **architecture:** Qwen3_5ForConditionalGeneration (qwen3_5), 64 layers
|
||
- **quantization:** compressed-tensors / mixed-precision — W8A8 (float-quantized), W4A4 (nvfp4-pack-quantized)
|
||
- **speculative decoding:** `{"method": "dflash", "model": "/drafter", "num_speculative_tokens": 7}`
|
||
- **image:** `vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013`
|
||
|
||
### `vllm-gen-small` — GPU 0
|
||
|
||
- **serves:** `gen-small`, `gen-small-thinking`
|
||
- **model:** `/tank/aimodels/qwen36-35b-a3b-heretic-nvfp4`
|
||
- **architecture:** Qwen3_5MoeForConditionalGeneration (qwen3_5_moe), 40 layers, 256 experts
|
||
- **quantization:** modelopt / None — W4A4 (None)
|
||
- **speculative decoding:** `{"method": "qwen3_5_mtp", "num_speculative_tokens": 3}`
|
||
- **image:** `vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013`
|
||
|
||
### `vllm-coder` — GPU 1
|
||
|
||
- **serves:** `qwen2.5-coder-1.5b`
|
||
- **model:** `?`
|
||
- **image:** `vllm/vllm-openai:v0.24.0`
|
||
|
||
### `vllm-embed` — GPU 1
|
||
|
||
- **serves:** `Qwen/Qwen3-Embedding-0.6B`
|
||
- **model:** `?`
|
||
- **image:** `vllm/vllm-openai:latest` ⚠ **floating tag**
|
||
|
||
### `vllm-erp-seat` — GPU 1
|
||
|
||
- **serves:** `G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16`
|
||
- **model:** `/tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16`
|
||
- **architecture:** Gemma4ForConditionalGeneration (gemma4), 30 layers, 128 experts
|
||
- **quantization:** compressed-tensors / nvfp4-pack-quantized — W4A16 (nvfp4-pack-quantized)
|
||
- **image:** `vllm/vllm-openai:nightly-311b3513af33bc29b4acb2fde2e9313e5e9966a0`
|
||
|
||
### `vllm-meromero-rp` — GPU 1
|
||
|
||
- **serves:** `char-rp`, `char-rp-thinking`
|
||
- **model:** `/tank/aimodels/meromero-v2-nvfp4-work/G4-MeroMero-v2-31B-NVFP4A16`
|
||
- **architecture:** Gemma4ForConditionalGeneration (gemma4), 60 layers
|
||
- **quantization:** compressed-tensors / nvfp4-pack-quantized — W4A16 (nvfp4-pack-quantized)
|
||
- **image:** `vllm/vllm-openai:v0.26.0`
|
||
|
||
### `vllm-rerank-a3` — GPU 1
|
||
|
||
- **serves:** `BAAI/bge-reranker-v2-m3`
|
||
- **model:** `?`
|
||
- **image:** `vllm/vllm-openai:v0.24.0`
|
||
|
||
### `vllm-reward` — GPU 1
|
||
|
||
- **serves:** `Skywork/Skywork-Reward-V2-Llama-3.1-8B-AWQ`
|
||
- **model:** `/tank/aimodels/llm/Skywork-Reward-V2-Llama-3.1-8B-AWQ`
|
||
- **architecture:** LlamaForSequenceClassification (llama), 32 layers
|
||
- **quantization:** compressed-tensors / pack-quantized — W4A16 (pack-quantized)
|
||
- **image:** `vllm/vllm-openai:latest` ⚠ **floating tag**
|
||
|
||
### `vllm-flash-next` — GPU 2
|
||
|
||
- **serves:** `qwen3.8-flash-next-uncensored`, `qwen3.8-flash-next-uncensored-thinking`
|
||
- **model:** `/tank/aimodels/qwen38-flash-next-orcarouter-nvfp4-plefp8`
|
||
- **architecture:** Qwen4ExpForConditionalGeneration (qwen4_exp), 48 layers, 512 experts
|
||
- **quantization:** compressed-tensors / mixed-precision — W8A16 (naive-quantized), W4A16 (nvfp4-pack-quantized)
|
||
- **speculative decoding:** `{"method": "mtp", "num_speculative_tokens": 3}`
|
||
- **image:** `vllm/vllm-openai:nightly-eed1f3d0c6043bd494424a22443ee198dd56f657`
|
||
|
||
## Gateway aliases resolving to this host
|
||
|
||
22 aliases. Ports with no listening seat are marked dead.
|
||
|
||
| alias | port |
|
||
|---|---|
|
||
| `char-rp` | 8016 |
|
||
| `char-rp-fast` | 8021 |
|
||
| `char-rp-reasoning` | 8016 |
|
||
| `chat-judge` | 8022 |
|
||
| `classifier` | 8026 |
|
||
| `classifier-large` | 8022 |
|
||
| `coder-fast` | 8020 |
|
||
| `erp-tune-v2` | 8098 |
|
||
| `gemma4-26b-a4b-it-base` | 8099 |
|
||
| `gen` | 8022 |
|
||
| `gen-large` | 8022 |
|
||
| `gen-reasoning` | 8022 |
|
||
| `gen-small` | 8026 |
|
||
| `gen-small-reasoning` | 8026 |
|
||
| `image-judge` | 8022 |
|
||
| `qwen-image-bench` | 8022 |
|
||
| `sec` | 8025 |
|
||
| `sec-reasoning` | 8025 |
|
||
| `summarizer` | 8026 |
|
||
| `summarizer-large` | 8022 |
|
||
|
||
---
|
||
|
||
*Lineage, provenance, model cards, measured tok/s and depth results live in the hand-curated companion [`llm-seat-catalog.md`](llm-seat-catalog.md).*
|
||
|
||
*Regenerate with `scripts/seat-inventory.py` after ANY seat change —
|
||
model swap, quant change, context or utilization edit, or speculative-decoding
|
||
change. Run `--check` in CI to catch a stale document.*
|
||
|
||
> **2026-09-25:** `qwen3-embedding` (:8001) and `reranker` (:8013) LEFT fv-ml1 —
|
||
> their vLLM seats were retired and the names now route to TEI on esh-ml1
|
||
> (`stacks/embed-rerank`). ~6.1 GB freed on GPU 1.
|