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RTX 5090 optimized ModelOpt NVFP4 conversion of orcarouter/Qwen3.8-27B-Uncensored, produced directly from the original BF16 safetensors. This checkpoint preserves the Qwen3.8 vision-language architecture and native MTP tensors. It is paired with the target-matched fleetml/Qwen3.8-27B-Uncensored-DSpark-RTX5090, now released in ModelOpt NVFP4. The validated Hermes serving profile launches with a 122,880-token context limit. SGLang automatically allocated an 87,798-token active pool and left 2.83 GB of GPU memory free after cache allocation and CUDA graph capture on one RTX 5090.

Visual QA
Input Text · Image→ Output Text
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
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1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

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Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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