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4 changes: 2 additions & 2 deletions .runpod/hub.json
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
{
"title": "Holo4 (Holo4-27B-GGUF, Holo4-35B-A3B-GGUF)",
"description": "Serve Holo4 (Holo4-27B-GGUF, Holo4-35B-A3B-GGUF) on Runpod Serverless with vLLM. Computer use agents are a fast growing self-host workload, and teams want them on their own GPUs for privacy and cost control over long screenshot-heavy loops. Two sizes cover different rentals: the 27B dense fits a single 48GB to 80GB card, while the 35B-A3B MoE runs cheap per token and scales well for parallel agent sessions. GGUF weights mean day-one llama.cpp and Ollama deploys with the hai-agents harness on Runpod.",
"title": "Holo4-35B-A3B",
"description": "Serve Holo4-35B-A3B (H Company) on Runpod Serverless with vLLM.",
"type": "serverless",
"category": "image",
"iconUrl": "https://www.runpod.io/favicon.ico",
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31 changes: 9 additions & 22 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,16 +1,16 @@
# Holo4 (Holo4-27B-GGUF, Holo4-35B-A3B-GGUF) on Runpod Serverless
# Holo4-35B-A3B on Runpod Serverless

[![Runpod](https://api.runpod.io/badge/runpod-workers/worker-holo4)](https://console.runpod.io/hub/runpod-workers/worker-holo4)

Serve Holo4 (Holo4-27B-GGUF, Holo4-35B-A3B-GGUF) (H Company) on Runpod Serverless with vLLM.
Serve Holo4-35B-A3B (H Company) on Runpod Serverless with vLLM.
License: apache-2.0.

## Recipe

| Setting | Value |
|---|---|
| Engine | vllm |
| Image | `runpod/worker-v1-vllm:v2.27.0` |
| Image | this repo's `Dockerfile`, on `vllm/vllm-openai:v0.29.0` |
| GPU | 1x RTX 6000 Ada |
| Precision | fp8 |
| Max model length | 8192 |
Expand All @@ -22,6 +22,7 @@ License: apache-2.0.
| `GPU_MEMORY_UTILIZATION` | `0.90` |
| `MAX_CONCURRENCY` | `30` |
| `MAX_MODEL_LEN` | `8192` |
| `MAX_NUM_SEQS` | `32` |
| `MODEL_NAME` | `Hcompany/Holo4-35B-A3B` |
| `QUANTIZATION` | `fp8` |
| `TENSOR_PARALLEL_SIZE` | `1` |
Expand All @@ -33,26 +34,12 @@ License: apache-2.0.
| 1x RTX 6000 Ada fp8 | $0.84 | 362.6 | 351.9 | 123.7 | $1.89 |

Cost per 1M output tokens is the hourly rate divided by measured throughput. It
assumes one saturated worker and no idle time, so treat it as a floor.
assumes one saturated worker and no idle time, so treat it as a floor. Measured by Launch
Builder on `runpod/worker-v1-vllm:v2.27.0` with the same model, GPU, precision and context
length; this worker runs vLLM v0.29.0.

## Deploy links

- Deploy on Runpod: https://console.runpod.io/deploy?template=yye0eu6dtk&utm_source=hub&utm_medium=product&utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf&utm_content=readme
- Model page: https://www.runpod.io/models/h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf?utm_source=hub&utm_medium=product&utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf&utm_content=readme
- Docs: https://docs.runpod.io/public-endpoints/models/h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf?utm_source=hub&utm_medium=product&utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf&utm_content=readme
- Deploy on Runpod: https://console.runpod.io/hub/runpod-workers/worker-holo4?utm_source=hub&utm_medium=product&utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf&utm_content=readme

Every link carries `utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf`. Keep it intact when you copy a link anywhere else.

## Before merging this bundle

Run the suite against a live endpoint:

```bash
node hub-test-suite.mjs --repo <owner>/<name> --prefix h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf- --create
```

## Fast path while this is in review

```bash
runpodctl serverless create --hub-id <vllm listing> --model-reference hf://Hcompany/Holo4-35B-A3B
```
The link carries `utm_campaign=202609_activation_ml-engineer_h-company-holo4-holo4-27b-gguf-holo4-35b-a3b-gguf`. Keep it intact when you copy a link anywhere else.
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