qwythos-9b-fp8cd-gdnvis-h100-vllm
Published Jul 25, 2026. Proof verified Jul 25, 2026.
1.29x faster
Median latency measured 1058 ms at baseline and 815 ms optimized.
Quality evidence
gsm8k 99.35% recovery, passed.
Model
Qwythos-9B-Claude-Mythos-5-1M measured packages and prices
RunInfra has published 1 measured package for empero-ai/Qwythos-9B-Claude-Mythos-5-1M on H100. Every package below keeps its engine, price, and proof date together.
Parameters
9B
Modality
Text
Base model license
Apache-2.0
Hugging Face model
The published packages are available to buy
| Package | GPU | Engine | Optimization | Price | Verified |
|---|---|---|---|---|---|
| qwythos-9b-fp8cd-gdnvis-h100-vllm | H100 | vLLM 0.25.1 | Channelwise FP8 weights, dynamic per-token activations | $20 one-time | Jul 25, 2026 |
What we measured
The recipe keeps the model's sensitive recurrent and vision paths at higher precision while applying channelwise FP8 elsewhere.
Published package measurements and prices for Qwythos-9B-Claude-Mythos-5-1M, grouped from the public RunInfra catalog.
Measured by RunInfra on H100 with vLLM 0.25.1; proof dates are listed with each package.
We report package measurements here, and each package remains subject to its listed license.
Citation: RunInfra (2026). Measured open-model serving benchmarks. https://runinfra.ai/catalog.
What is not measured
Other GPU measurements for this model not published.
Other engine measurements for this model not published.
Measurements for context lengths not listed in these packages not published.
Published facts answer common questions
What does Qwythos-9B-Claude-Mythos-5-1M cost on RunInfra?
qwythos-9b-fp8cd-gdnvis-h100-vllm is listed at $20 one-time, published Jul 25, 2026.
Which GPU serves Qwythos-9B-Claude-Mythos-5-1M?
qwythos-9b-fp8cd-gdnvis-h100-vllm is measured on H100 with vLLM 0.25.1. Proof verified Jul 25, 2026.
Is quality measured for Qwythos-9B-Claude-Mythos-5-1M?
gsm8k 99.35% recovery, passed. Proof verified Jul 25, 2026.
If you need custom optimization for a specific model, describe what you need
End-to-end encryption
Isolated GPU infrastructure
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