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PAW-125B-FLASH-NEXT-X3.1

lackonendes

_If this model is useful to you, support the work by following @nawariokra on X, or buy me a coffee on Ko-fi._ **`Qwen/Qwen3.8-Flash-Next` (125B MoE, 6B active) on one or two 24 GB GPUs plus CPU, with the full 262,144-token context.** Two GGUF shards: **47.5 GiB of weights** and a 48.3 GiB n-gram table (95.8 GiB in all). It runs on our own engine TRUSS. **Images:** `flashnext-mmproj-f16.gguf` is the Qwen3.8-Flash-Next vision encoder (Qwen3-VL style). With it the server takes `image_url` parts next to text: a 448x448 picture is 196 tokens, the long side is capped at 1,344 (1,764 tokens). Give the ViT its own card and start the server with `--mmproj`; see SERVING.md.

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PAW-24B-X3.1

lackonendes

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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PAW-27B-GGUF

lackonendes

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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PAW-27B-X3.1-GGUF

lackonendes

_If this model is useful to you, support the work by following @nawariokra on X, or buy me a coffee on Ko-fi._ Run `Qwen/Qwen3.8-27B` with good quality on a single RTX 3090 (24 GB VRAM) at full 262,144-token context — 129 tok/s generation, up to 1268 tok/s prompt processing. This is an update to our earlier PAW-27B-X3 release, with lower quality loss at the same file sizes. Two example scenes, generated in one shot from a text prompt (three.js/WebGL code, output by this model, rendered in a browser):

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PAW-27B-X3-GGUF

lackonendes

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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PAW-35B-A3B-GGUF

lackonendes

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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PAW-763B-X3

lackonendes

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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PAW-763B-X3.1

lackonendes

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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Visual QA

Input Text · Image→ Output Text

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COST EXPLORER

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Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 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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Selection guide & FAQ

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.

Do open weights mean free commercial use?+

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

Is the top-ranked model the best for me?+

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

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Explore AI models 8

PAW-125B-FLASH-NEXT-X3.1

PAW-24B-X3.1

PAW-27B-GGUF

PAW-27B-X3.1-GGUF

PAW-27B-X3-GGUF

PAW-35B-A3B-GGUF

PAW-763B-X3

PAW-763B-X3.1

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