RVN Qwen3.8 Flash Next Abliterated Uncensored — Hardware Requirements & GPU Compatibility
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RVN Qwen3.8 Flash Next Abliterated Uncensored is a 176.9B-parameter open language model from 0bserverx in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 106.55 GB of VRAM — see which GPUs and Macs can run it below.
RVN Qwen3.8 Flash Next Abliterated Uncensored runs on a 128 GB+ Mac or a datacenter GPU
Best local pick → Mac Pro M2 Ultra (128 GB) · Q4_K_M · 107.1 GB · ~14 tok/s
Macs from 96 GB (Q3_K_L · ~16 tok/s)
Other
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run RVN Qwen3.8 Flash Next Abliterated Uncensored
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
ollama run hf.co/0bserverx/RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored-GGUF:Q4_K_MQ4_K_M runs on one Instinct MI250X 128 GB · 16K context
Download: RVN-Qwen3.8-Flash-Next-Q4_K_M-00001-of-00008.gguf119.15 GB + 7 parts0bserverx
Other ways
each opens step-by-stepRun in cloud
Fits on H200 (141 GB) (33 GB headroom) · Q4_K_M
- Generation speed
- ~72 tok/s
- generation speed
- Cost per 1M output tokens
- $13.89
- per 1M output tokens
How Much VRAM Does RVN Qwen3.8 Flash Next Abliterated Uncensored Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 75.6 GB | 76.9 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Runs on H100 SXM 80 GB | |
| 77.8 GB | 79.1 GB | 3-bit small — 3-bit small quantization | Runs on H100 SXM 80 GB | |
| 86.6 GB | 87.9 GB | 3-bit medium — 3-bit medium quantization | Runs on RTX PRO 6000 Blackwell Max-Q Workstation Edition 96 GB | |
| 88.9 GB | 90.1 GB | 4-bit · legacy — 4-bit legacy quantization | Runs on RTX PRO 6000 Blackwell Max-Q Workstation Edition 96 GB | |
| 106.5 GB | 107.8 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Runs on Instinct MI250X 128 GB | |
| 126.5 GB | 127.7 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Runs on Instinct MI250X 128 GB | |
| 146.4 GB | 147.6 GB | 6-bit, very good — 6-bit quantization, very good quality | Runs on B200 192 GB | |
| 177.3 GB | 178.6 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Runs on B200 192 GB |
Selected Q4_K_M
4-bit medium quantization107.1GBat 16K context
- Weights
- 106.2 GB
- KV cache
- 0.7 GB
- Overhead
- 0.3 GB
Server-class: ~107.1 GB at 16K context · one Instinct MI250X 128 GB
Which Hardware Can Run RVN Qwen3.8 Flash Next Abliterated Uncensored?
Q4_K_M · 106.5 GBRVN Qwen3.8 Flash Next Abliterated Uncensored (Q4_K_M) requires 106.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 139+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 117.2 GB. No consumer GPU has enough memory. 18 devices with unified memory can run RVN Qwen3.8 Flash Next Abliterated Uncensored, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Pro M2 Ultra (128 GB).
96 GB
Q4_K_M · best fit Q3_K_L (91.7 GB)
3 GPUs · 2 Mac classes
RTX PRO 6000 Blackwell Max-Q Workstation Edition~35Simulate output on RTX PRO 6000 Blackwell Max-Q Workstation EditionRTX PRO 6000 Blackwell Workstation Edition~35Simulate output on RTX PRO 6000 Blackwell Workstation EditionRTX PRO 6000 Blackwell Server Edition~32Simulate output on RTX PRO 6000 Blackwell Server EditionM3 Ultra*96 GB~16Simulate output on Mac Studio (M3 Ultra, 96GB)M3 Max*96 GB~7Simulate output on MacBook Pro 14" M3 Max (96 GB)128–144 GB
fits · 20.9 GB free · up to 256K ctx
4 GPUs · 2 Mac classes · 2 device families
GH200 Grace Hopper Superchip~73Simulate output on GH200 Grace Hopper SuperchipH200 NVL~72Simulate output on H200 NVLH200 SXM~72Simulate output on H200 SXMM2 Ultra*128 GB~14Simulate output on Mac Pro M2 Ultra (128 GB)M5 Max128 GB~11Simulate output on Mac Studio M5 Max (128 GB)GB10~5Simulate output on NVIDIA DGX SparkJetson T5000 (Thor)~5Simulate output on NVIDIA Jetson AGX Thor Developer Kit192+ GB
fits · 84.9 GB free · up to 256K ctx
6 GPUs · 1 Mac class · 2 device families
B200~106Simulate output on B200B300~106Simulate output on B300Instinct MI350X~59Simulate output on Instinct MI350XM3 Ultra*256–512 GB~14Simulate output on Mac Studio (M3 Ultra, 256GB)8x H100 SXM5~215Simulate output on NVIDIA DGX H1008x A100 SXM4~168Simulate output on NVIDIA DGX A100 640GB
By VRAM tier · typical GPUs and Macs at Q4_K_M
Consumer GPUs (up to 32 GB) and Macs up to 64 GB: too small for this model (needs ≥ 74 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Alternatives to RVN Qwen3.8 Flash Next Abliterated Uncensored
Qwen 3.8 family · 12 models →Similar models
2| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| DeepSeek V4 Flash DSparkDeepSeek | — | 99.6 GB | —needs > 24 GB | same size |
| BloomBigScience | — | 122.4 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- 0bserverx
- Family
- Qwen 3.8
- Parameters
- 176.9B
- Active parameters
- 58.5B per token
- Architecture
- Qwen4ExpForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-08-31
- License
- Other
Frequently Asked Questions
How much VRAM does RVN Qwen3.8 Flash Next Abliterated Uncensored need?
RVN Qwen3.8 Flash Next Abliterated Uncensored requires 106.5 GB of VRAM at Q4_K_M, or 354.3 GB at BF16. Full 262K context adds up to 10.7 GB (117.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 176.9B × 4.8 bits ÷ 8 = 106.2 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 11 GB (at full 262K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run RVN Qwen3.8 Flash Next Abliterated Uncensored?
No — RVN Qwen3.8 Flash Next Abliterated Uncensored requires at least 73.4 GB at IQ3_XS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
What's the best quantization for RVN Qwen3.8 Flash Next Abliterated Uncensored?
For RVN Qwen3.8 Flash Next Abliterated Uncensored, Q4_K_M (106.5 GB) offers the best balance of quality and VRAM usage. Q5_0 (111.0 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XS at 73.4 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run RVN Qwen3.8 Flash Next Abliterated Uncensored on a Mac?
Yes — Mac Studio (M3 Ultra, 96GB) and 20 other Macs can run RVN Qwen3.8 Flash Next Abliterated Uncensored, the smallest at Q3_K_L. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 106.5 GB of usable unified memory (RAM minus macOS overhead), from Mac Pro M2 Ultra (128 GB).
Can I run RVN Qwen3.8 Flash Next Abliterated Uncensored locally?
Yes — RVN Qwen3.8 Flash Next Abliterated Uncensored can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is RVN Qwen3.8 Flash Next Abliterated Uncensored?
At Q4_K_M, RVN Qwen3.8 Flash Next Abliterated Uncensored can reach ~59 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = 1000 ÷ (active GB ÷ (bandwidth GB/s × efficiency) × 1000 + layers × routing ms)
Mixture-of-Experts: just the active experts get read for each token, along with a fixed routing cost per layer.
Example: NVIDIA B200 → 35.2 GB active ÷ (8000 × 0.65) = 6.78 ms, plus 48 layers × 0.055 ms = 2.64 ms, so 1000 ÷ 9.42 ms = ~106 tok/s
Estimated speed at Q4_K_M (106.5 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of RVN Qwen3.8 Flash Next Abliterated Uncensored?
At Q4_K_M, the download is about 106.17 GB. The full-precision BF16 version is 353.89 GB. The smallest option (IQ3_XS) is 72.99 GB.
Which GPUs can run RVN Qwen3.8 Flash Next Abliterated Uncensored?
No single consumer GPU has enough VRAM to run RVN Qwen3.8 Flash Next Abliterated Uncensored at Q4_K_M (106.5 GB). Multi-GPU or professional hardware is required.
Which devices can run RVN Qwen3.8 Flash Next Abliterated Uncensored?
18 devices with unified memory can run RVN Qwen3.8 Flash Next Abliterated Uncensored at Q4_K_M (106.5 GB), including ASUS Ascent GX10, Mac Pro M2 Ultra (128 GB), Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.