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Qwen · open-weights

Qwen3.8 Flash Next

Qwen3.8 Flash Next is an open-weights language model from Qwen, released August 24, 2026. It has 125B parameters (mixture-of-experts, 6B active). The context window is 256K tokens.

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Lab
Qwen
Released
August 24, 2026
Weights
Open qwen-community-1.0
Parameters
125B MoE · 6B active
Context
256K
Price / M tokens
–
Epoch ECI
not yet rated

Can you run Qwen3.8 Flash Next locally?

The smallest common GPU it runs on is 8 GB of VRAM (with 32 GB of RAM): IQ2_XXS, GPU + experts in RAM, roughly 43 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMToo large––––
8 GB VRAMRuns · GPU + CPU expertsIQ2_XXS (heavy loss)7.2 GB26.0 GB~43
12 GB VRAMRuns via StrataStrata pack–22.0 GB~51
16 GB VRAMRuns via StrataStrata pack–18.0 GB~62
24 GB VRAMRuns via StrataStrata pack–25.6 GB~52
32 GB VRAMRuns via StrataStrata pack–17.6 GB~73

Ready-made quantizations on Hugging Face: ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF · unsloth/Qwen3.8-Flash-Next-GGUF · agentionai/Qwen3.8-Flash-Next-Gyro-GGUF · orcarouter/Qwen3.8-Flash-Next-Uncensored-GGUF · huihui-ai/Huihui-Qwen3.8-Flash-Next-abliterated-v2-GGUF · ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF

Benchmark results

Epoch AI has not published results for Qwen3.8 Flash Next yet. New models are usually evaluated within days to weeks.

Links

Hugging Face: Qwen/Qwen3.8-Flash-Next · Strata

More from Qwen

Qwen3.8 Omni Flash · Qwen3.8 Max (0902) · Qwen3.8 Flash · Qwen 3.8 27B · Qwen3.8-2.4T-A95B · Qwen 3.8 Max · Qwen3.7 Flash · Qwen3.7-Plus

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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