Qwen3.8-Flash-Next
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
55.8
AA Index
Agentic
56.4
AA Index
Intelligence Index - Qwen3.8-Flash-Next vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-08-31.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA | 92.3 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
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Deep dive
Notes, sources, and the full write-up
Qwen3.8-Flash-Next is a 180B-parameter other model from Alibaba. It scores 55.8 on the Artificial Analysis Intelligence Index. At Q4_K_M it needs roughly 104 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Qwen3.8-Flash-Next vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Qwen3.8-Flash-Next | 55.8 | - | 92.3 |
| Claude Opus 5 (max) | 63.1 | - | 93.2 |
| Claude Fable 5 (with fallback) | 62.1 | - | 92.6 |
| GPT-5.6 Sol (max) | 60.9 | - | 94.1 |
| Grok 4.6 (high) | 60.9 | - | 94.9 |
| Qwen3.8 Max | 58.1 | - | 92.7 |
Source: Artificial Analysis (2026-08-29).
Popularity
Qwen3.8-Flash-Next has 4,810 downloads in the last month on HuggingFace and 4,179 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Qwen3.8-Flash-Next need?
Qwen3.8-Flash-Next with 180B parameters needs approximately 104 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Qwen3.8-Flash-Next better than other Qwen models?
Qwen3.8-Flash-Next has 180B parameters with 262,144 context - a strong choice for general use.
What license is Qwen3.8-Flash-Next under?
Qwen3.8-Flash-Next is released under the other license, making it suitable for most commercial and personal projects.
What hardware runs Qwen3.8-Flash-Next well?
With 180B parameters, Qwen3.8-Flash-Next requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Qwen3.8-Flash-Next?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~128 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Qwen3.8-Flash-Next's context window handle?
Qwen3.8-Flash-Next supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next competes with other 90B–270B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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