DeepSeek V4.1 Flash 552B vs Qwen3.8-Flash-Next
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Qwen3.8-Flash-Next is more hardware-efficient: it needs 123.0 GB at its Q4_K_M build vs 571.6 GB for DeepSeek V4.1 Flash 552B's Q4_K_M, fitting on 22 GPUs natively.
Analysis
DeepSeek V4.1 Flash and Qwen3.8-Flash-Next both market an indexer-style attention trick for cheaper long context, the same pairing this site's existing Qwen3.8-Flash-Next comparisons already draw against V4.1 Flash's predecessors, and the outcome repeats here even more sharply: DeepSeek's compression genuinely shrinks what gets stored, Qwen's narrows compute but not storage. Qwen3.8-Flash-Next is also explicitly a preview of a future architecture, not a finished release, while V4.1 Flash, though only released the same day this comparison was written, is DeepSeek's actual production checkpoint.
Restricted to the 262,144-token context Qwen3.8-Flash-Next tops out at (a quarter of V4.1 Flash's own 1,048,576-token ceiling), the KV-cache gap is stark: V4.1 Flash needs 0.6 GB, Qwen3.8-Flash-Next needs 6.4 GB, more than 10x as much, because Qwen Sparse Attention narrows what a query attends to for compute while still drawing from the same full per-token cache a dense layer would need, per Qwen's own technical report. On the one benchmark field both report, they're close: GPQA Diamond 91.7 for Qwen against 90.9 for V4.1 Flash. Weights run in Qwen's favor on paper: this site's generic ladder puts Qwen3.8-Flash-Next's Q4_K_M at 109.6 GB, though no confirmed community build exists for this preview checkpoint either, against V4.1 Flash's floored ~510 GB, confirmed as the only real download that exists rather than an estimate. Licensing differs: DeepSeek ships MIT with no conditions, while Qwen's Community 1.0 terms require a separate license for any Model-as-a-Service or 'AI Work Assistant' business. Both accept image input; Qwen also accepts video, which V4.1 Flash's card doesn't claim.
Bottom line: Neither model is a realistic local pick today: Qwen3.8-Flash-Next is an explicit architecture preview with no confirmed quant build, and V4.1 Flash's only download is a ~510 GB native checkpoint that doesn't fit any machine this site tracks. As API-only choices the two are close on the one benchmark that overlaps, with V4.1 Flash's real production status and much smaller KV cache the more compelling case, while Qwen3.8-Flash-Next is worth watching mainly as a preview of what Alibaba's next generation looks like, with the finished 'Qwen3.8-Flash' still to follow.
Total vs. active parameters: V4.1 Flash is bigger on both axes
Both models are MoE, so total parameters (the VRAM bill) and active parameters (the compute bill) move independently. V4.1 Flash routes through a larger slice of a much larger model.
Two different 'sparse attention' tricks, one real cache saving
Both models market an indexer that scores context in blocks, but only one of them actually shrinks what gets stored, the same distinction this site's other Qwen3.8-Flash-Next comparisons draw against DeepSeek's earlier Flash releases, restricted here to the 262,144-token window both can reach.
KV cache only, at FP16. Weights and activation overhead sit on top of these figures.
At 262,144 tokens, V4.1 Flash's Causal Encoder-Decoder design keeps its KV cache at 0.6 GB. Qwen3.8-Flash-Next's Qwen Sparse Attention, which narrows compute rather than storage per Qwen's own technical report, needs 6.4 GB for the same context, more than 10x as much, even though V4.1 Flash's real context ceiling continues four times further before it needs the trick at all.
VRAM at each quantization (8k context)
| Quant | DeepSeek V4.1 Flash 552B | Qwen3.8-Flash-Next | Diff |
|---|---|---|---|
| FP32 | 2473.0 GB | 806.6 GB | +207% |
| BF16 | 1236.5 GB | 403.4 GB | +206% |
| FP16 | 1236.5 GB | 403.4 GB | +206% |
| Q8_0 | 657.2 GB | 214.5 GB | +206% |
| Q6_K | 571.6 GB | 165.7 GB | +245% |
| Q5_K_M | 571.6 GB | 143.8 GB | +298% |
| Q4_K_M | 571.6 GB | 123.0 GB | +365% |
| Q3_K_M | 571.6 GB | 97.2 GB | +488% |
| Q2_K | 571.6 GB | 77.0 GB | +642% |
| NVFP4 | 571.6 GB | 101.0 GB | +466% |
Diff is DeepSeek V4.1 Flash 552B relative to Qwen3.8-Flash-Next. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | DeepSeek V4.1 Flash 552B | Qwen3.8-Flash-Next |
|---|---|---|
| Org | DeepSeek | Alibaba |
| Parameters | 552B | 180B |
| Architecture | MoE (16B active) | MoE (6B active) |
| Context | 1024k tokens | 256k tokens |
| Modalities | text, vision | text, vision, video |
| License | MIT | Qwen Community 1.0 |
| Commercial | Yes | Yes |
| Released | 2026-09-10 | 2026-08-26 |
| GPUs (native) | 0 / 119 | 22 / 119 |
Benchmark scores
| Benchmark | DeepSeek V4.1 Flash 552B | Qwen3.8-Flash-Next |
|---|---|---|
| GPQA Diamond | 90.9 | 91.7 |
| Terminal-Bench 2.1 | 90.6 | N/A |
Green = higher score (better). N/A = not yet available. ~ = inherited from a base model, not independently reported for that release itself.
GPUs that run only DeepSeek V4.1 Flash 552B(0)
Every GPU that runs DeepSeek V4.1 Flash 552B also runs Qwen3.8-Flash-Next.
GPUs that run only Qwen3.8-Flash-Next(22)
- NVIDIA B300 288GB288 GB
- NVIDIA B200 180GB180 GB
- NVIDIA H200 141GB141 GB
- NVIDIA RTX Pro 600096 GB
- NVIDIA DGX Spark (128GB)128 GB
- AMD Instinct MI300X192 GB
- AMD Strix Halo (128GB)128 GB
- AMD Strix Halo (96GB)96 GB
- Apple M5 Ultra (512GB)512 GB
- Apple M5 Ultra (256GB)256 GB
- +12 more
Which should you use?
- • You want maximum capability and have a 572 GB+ GPU
- • Long context matters: it supports 1024k tokens vs 256k
- • It's the newer release (2026-09-10 vs 2026-08-26); check the benchmark table above for what actually improved
- • You have limited VRAM: it's a smaller model needing 123.0 GB vs 571.6 GB
Frequently asked questions
- Which is better, DeepSeek V4.1 Flash 552B or Qwen3.8-Flash-Next?
- DeepSeek V4.1 Flash 552B has 552B parameters vs 180B for Qwen3.8-Flash-Next, so DeepSeek V4.1 Flash 552B is the larger model. Qwen3.8-Flash-Next is more hardware-efficient, needing 123.0 GB at its Q4_K_M build vs 571.6 GB for DeepSeek V4.1 Flash 552B's Q4_K_M. Qwen3.8-Flash-Next runs on more GPUs natively (22 vs 0).
- How much VRAM does DeepSeek V4.1 Flash 552B need vs Qwen3.8-Flash-Next?
- At 8k context, DeepSeek V4.1 Flash 552B needs approximately 571.6 GB of VRAM at its Q4_K_M build, while Qwen3.8-Flash-Next needs 123.0 GB at its Q4_K_M build. At the largest build each ships, DeepSeek V4.1 Flash 552B requires 1236.5 GB (FP16) vs 403.4 GB (FP16) for Qwen3.8-Flash-Next.
- Can you run DeepSeek V4.1 Flash 552B on the same GPUs as Qwen3.8-Flash-Next?
- These models have very different VRAM requirements, so they do not share the same compatible GPU set.
- What is the difference between DeepSeek V4.1 Flash 552B and Qwen3.8-Flash-Next?
- DeepSeek V4.1 Flash 552B has 552B parameters (16B active, MoE) with a 1024k context window. Qwen3.8-Flash-Next has 180B parameters (6B active, MoE) with a 256k context window. Licensing differs: DeepSeek V4.1 Flash 552B is MIT while Qwen3.8-Flash-Next is Qwen Community 1.0.
- Which model fits in 24 GB of VRAM, DeepSeek V4.1 Flash 552B or Qwen3.8-Flash-Next?
- Neither fits in 24 GB: DeepSeek V4.1 Flash 552B needs 571.6 GB at Q4_K_M and Qwen3.8-Flash-Next needs 123.0 GB at Q4_K_M. Both require a multi-GPU server with 572 GB+ of combined VRAM.
- Which handles long context better, DeepSeek V4.1 Flash 552B or Qwen3.8-Flash-Next?
- At 262,144 tokens, V4.1 Flash's Causal Encoder-Decoder design keeps its KV cache at 0.6 GB. Qwen3.8-Flash-Next's Qwen Sparse Attention, which narrows compute rather than storage per Qwen's own technical report, needs 6.4 GB for the same context, more than 10x as much, even though V4.1 Flash's real context ceiling continues four times further before it needs the trick at all.