Qwen3.8 Flash Next
176B total but only 6B active — the most extreme sparsity ratio in this catalogue. That makes it unusually fast on low-bandwidth unified-memory machines like the DGX Spark and Strix Halo, where a dense model of comparable quality would be unusable.
Alibaba QwenMixture of expertsagenticreasoning10 machines can run it
Total parameters
180B
Official spec sets memory need
Active parameters
6B
Official spec sets decode speed
Context
256K
Official spec tokens
4-bit weights
98 GB
Calculated before KV cache
This is a sparse mixture of experts. All 180B of weights must be available to the runtime, but only 6B are read per generated token. Ordinary runtimes keep the full quantized model in memory; a runtime-specific SSD-streaming artifact can retain a smaller working set and fetch expert data on demand, trading speed for capacity.
Model specification
Publisher
Alibaba Qwen Official spec
Architecture
Sparse mixture of experts Official spec
Total parameters
180B Official spec
Active parameters
6B per token Official spec
Context length
262,144 tokens Official spec
Attention ⓘ
HYBRID_LINEAR · 2 KV heads × 256 dim × 48 layers Official spec
Licence
Qwen Community 1.0 Official spec source
Specification confidence ⓘ
High · verified 2026-10-19 Official spec source
Released
1 Aug 2026 Official spec
Official source
Quantizations and memory
| Quantization | Format | Bits/weight | Resident | Download | Quality kept |
|---|---|---|---|---|---|
MLX 4-bit | mlx | 4.5 | 98.1 GB | 98.1 GB | 98.0% |
Q4_K_Mdefault | gguf | 4.85 | 104.7 GB | 104.7 GB | 98.5% |
Q5_K_M | gguf | 5.69 | 122.8 GB | 122.8 GB | 99.3% |
Q8_0 | gguf | 8.5 | 181.7 GB | 181.7 GB | 99.9% |
BF16 | safetensors | 16 | 335.3 GB | 335.3 GB | 100.0% |
Generic weight sizes are computed from the parameter count and bits per weight plus a format-specific overhead. Runtime-specific artifacts use their published resident and download footprints; streamed models can therefore require much more disk than memory. Quality retention is an assumption, not a measured evaluation.
Coding & quality benchmarksCompare coding results →
No published benchmark results have been imported for this model yet. This is missing evidence, not a score of zero.
We show source metrics rather than deriving one opaque quality number. Different benchmarks measure genuinely different things, and collapsing them into a single score would hide exactly the disagreements worth seeing.
Recommendations
Cheapest that can run it
~7.3–10.5 t/s · $1,531
Lowest purchase price among configurations where the model fits at some quantization in our catalogue. Speed is not considered.
Cheapest above 20 t/s
~97.9–141 t/s · $4,323
20 tokens/second is roughly the point at which generation keeps pace with reading. Below it, interactive use feels like waiting.
Cheapest above 40 t/s
~97.9–141 t/s · $4,323
40 tokens/second is the threshold most people describe as comfortable for coding agents, where output arrives faster than you can review it.
Fastest with real measurements
Nothing in the database qualifies.
Highest throughput among configurations with an actual published measurement rather than our estimate.
Best throughput per purchase-price unit
~97.9–141 t/s · $4,323
Highest decode tokens/second per 1,000 units of the displayed purchase currency. Ignores running costs and resale — see the economics section for the full picture.
Hardware that runs Qwen3.8 Flash Next0 measured, 10 estimated
10 of 10 rows
| Hardware↕ | Quant | Memory↕ | Decode▼ | Prefill↕ | Context | Price↕ | Fit | Confidence↕ |
|---|---|---|---|---|---|---|---|---|
| NVIDIA DGX H200 (8x H200, 1,128 GB) NVIDIA · 1,128 GB · 38,400 GB/s | Q8_0recommended | 191.1 GB | ~490–705 t/s | ~81420–169100 t/s | 256K | $359,430 | Comfortable | Estimated |
| Dell Precision 7960 Rack (2x RTX PRO 6000, 192 GB) Dell · 192 GB · 3,584 GB/s | Q5_K_Mrecommended | 128.1 GB | ~196–282 t/s | ~1950–4060 t/s | 256K | $36,663 | Comfortable | Estimated |
| Lenovo ThinkStation PX (4x RTX PRO 6000, 384 GB) Lenovo · 384 GB · 7,168 GB/s | Q8_0recommended | 189.5 GB | ~195–281 t/s | ~3910–8120 t/s | 256K | $58,553 | Comfortable | Estimated |
| Mac Studio M5 Ultra 256 GB Apple · 256 GB · 1,200 GB/s | Q5_K_Mrecommended | 127.7 GB | ~142–204 t/s | ~883–1830 t/s | 256K | $8,647 | Comfortable | Estimated |
| NVIDIA DGX Station GB300 (748 GB) NVIDIA · 748 GB · 7,100 GB/s | Q8_0recommended | 188.3 GB | ~102–147 t/s | ~10880–22590 t/s | 256K | $90,082 | Comfortable | Estimated |
| Mac Studio M5 Ultra 512 GB Apple · 512 GB · 1,200 GB/s | Q8_0recommended | 188.3 GB | ~101–145 t/s | ~883–1830 t/s | 256K | $11,350 | Comfortable | Estimated |
| Mac Studio M5 Max 128 GB Apple · 128 GB · 614 GB/s | MLX 4-bitrecommended | 102.2 GB | ~97.9–141 t/s | ~442–917 t/s | 128K | $4,323 | Borderline | Estimated |
| Mac Studio M3 Ultra 256 GB Apple · 256 GB · 819 GB/s | Q5_K_Mrecommended | 127.7 GB | ~84.9–122 t/s | ~213–442 t/s | 256K | $5,674 | Comfortable | Estimated |
| Mac Studio M3 Ultra 512 GB Apple · 512 GB · 819 GB/s | Q8_0recommended | 188.3 GB | ~58.9–84.7 t/s | ~213–442 t/s | 256K | $8,287 | Comfortable | Estimated |
| CPU-only workstation (Ryzen 9950X, 192 GB DDR5) Generic · 192 GB · 90 GB/s | Q5_K_Mrecommended | 127.7 GB | ~7.3–10.5 t/s | ~12.7–26.3 t/s | 256K | $1,531 | Comfortable | Estimated |
Submit a benchmarkContributions are reviewed before publication.
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