DeepSeek V4.1 Flash 552B vs GLM-5.3-Flash 320B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
GLM-5.3-Flash 320B is more hardware-efficient: it needs 218.5 GB at its Q4_K_M build vs 571.6 GB for DeepSeek V4.1 Flash 552B's Q4_K_M, fitting on 8 GPUs natively.
Analysis
DeepSeek V4.1 Flash and GLM-5.3-Flash are the two newest small-MoE 'Flash'-branded checkpoints from rival labs, released sixteen days apart in the same window, and both are the first natively multimodal release in their respective lineages. The comparison is close on capability and lopsided on availability: GLM-5.3-Flash has a real quantization table today, and V4.1 Flash, released the same day this comparison was written, does not.
The two land close in total size, 552B against 320B, but GLM-5.3-Flash actually activates more per token despite being the smaller model on disk, 18B against V4.1 Flash's 16B. Their attention designs solve the long-context problem differently: GLM-5.3-Flash mixes 34 linear-attention layers with 11 DeepSeek-style sparse-attention/MLA layers, only the latter caching at all, while V4.1 Flash's Causal Encoder-Decoder compresses across its whole 40-layer stack. The outcome favors V4.1 Flash by a wide margin at the full shared 1,048,576-token context both models support: 2.3 GB of KV cache against GLM-5.3-Flash's 23.6 GB, a roughly 10x gap. Benchmarks are nearly tied where they overlap: GPQA Diamond 90.9 for V4.1 Flash against 91.2 for GLM-5.3-Flash (Artificial Analysis's independently-run figure, since Z.ai doesn't publish GPQA itself), while Terminal-Bench 2.1 favors V4.1 Flash, 90.6 against 84.3, both vendors' own reported numbers. Both ship under MIT. Weights are the sharpest divide: this site's generic quantization ladder puts GLM-5.3-Flash's Q4_K_M at 194.9 GB, while V4.1 Flash has no build below its native ~510 GB release, confirmed against the actual published checkpoint rather than estimated, so its quantization table floors every rung at that number instead of a guess.
Bottom line: GLM-5.3-Flash is the practical local pick today: a 512 GB-class unified-memory machine holds even this site's generic Q4_K_M estimate with room for the KV cache, while V4.1 Flash's only existing download doesn't fit any single machine this site tracks. On raw capability the two are close enough that it's a coin flip either way, GLM-5.3-Flash edges ahead on GPQA, V4.1 Flash pulls well ahead on Terminal-Bench and has the smaller KV cache by a wide margin, so if local deployment isn't the constraint, either is a reasonable pick, and V4.1 Flash's coding-agent lean makes it the better bet through the API specifically.
Total vs. active parameters: the smaller model activates more
Both models are MoE. V4.1 Flash is the bigger checkpoint by total parameters, but GLM-5.3-Flash activates a larger slice of its own, smaller total, so the compute-per-token gap is narrower than the VRAM-bill gap suggests.
Two different multimodal 'Flash' releases, very different KV-cache shapes
Both models keep a caching subset of their layers rather than caching every layer, but the ratio and the design underneath it differ enough that the two end up in very different places at the same context length.
KV cache only, at FP16. Weights and activation overhead sit on top of these figures.
At the full 1,048,576-token window both models support, V4.1 Flash's KV cache is 2.3 GB against GLM-5.3-Flash's 23.6 GB, roughly a 10x gap, even though GLM-5.3-Flash already caches only 11 of its 45 layers.
DeepSWE v1.1: V4.1 Flash ahead by double digits
DeepSWE v1.1 has no field in this site's benchmark schema; both vendors report it in their own release notes for these exact checkpoints.
Z.ai's GLM-5.3-Flash release chart and DeepSeek's own API changelog (api-docs.deepseek.com/updates), both self-reported by the respective vendor; independent reproduction was not yet available for either figure at time of writing.
VRAM at each quantization (8k context)
| Quant | DeepSeek V4.1 Flash 552B | GLM-5.3-Flash 320B | Diff |
|---|---|---|---|
| FP32 | 2473.0 GB | 1433.8 GB | +72% |
| BF16 | 1236.5 GB | 717.0 GB | +72% |
| FP16 | 1236.5 GB | 717.0 GB | +72% |
| Q8_0 | 657.2 GB | 381.2 GB | +72% |
| Q6_K | 571.6 GB | 294.4 GB | +94% |
| Q5_K_M | 571.6 GB | 255.4 GB | +124% |
| Q4_K_M | 571.6 GB | 218.5 GB | +162% |
| Q3_K_M | 571.6 GB | 172.6 GB | +231% |
| Q2_K | 571.6 GB | 136.8 GB | +318% |
| NVFP4 | 571.6 GB | 179.4 GB | +219% |
Diff is DeepSeek V4.1 Flash 552B relative to GLM-5.3-Flash 320B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | DeepSeek V4.1 Flash 552B | GLM-5.3-Flash 320B |
|---|---|---|
| Org | DeepSeek | Z.ai |
| Parameters | 552B | 320B |
| Architecture | MoE (16B active) | MoE (18B active) |
| Context | 1024k tokens | 1024k tokens |
| Modalities | text, vision | text, vision, video |
| License | MIT | MIT |
| Commercial | Yes | Yes |
| Released | 2026-09-10 | 2026-08-25 |
| GPUs (native) | 0 / 119 | 8 / 119 |
Benchmark scores
| Benchmark | DeepSeek V4.1 Flash 552B | GLM-5.3-Flash 320B |
|---|---|---|
| GPQA Diamond | 90.9 | 91.2 |
| Terminal-Bench 2.1 | 90.6 | 84.3 |
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 GLM-5.3-Flash 320B.
GPUs that run only GLM-5.3-Flash 320B(8)
- NVIDIA B300 288GB288 GB
- NVIDIA B200 180GB180 GB
- AMD Instinct MI300X192 GB
- Apple M5 Ultra (512GB)512 GB
- Apple M5 Ultra (256GB)256 GB
- Apple M3 Ultra (512GB)512 GB
- Apple M3 Ultra (256GB)256 GB
- Apple M2 Ultra (192GB)192 GB
Which should you use?
- • You want maximum capability and have a 572 GB+ GPU
- • It's the newer release (2026-09-10 vs 2026-08-25); check the benchmark table above for what actually improved
- • You have limited VRAM: it's a smaller model needing 218.5 GB vs 571.6 GB
Frequently asked questions
- Which is better, DeepSeek V4.1 Flash 552B or GLM-5.3-Flash 320B?
- DeepSeek V4.1 Flash 552B has 552B parameters vs 320B for GLM-5.3-Flash 320B, so DeepSeek V4.1 Flash 552B is the larger model. GLM-5.3-Flash 320B is more hardware-efficient, needing 218.5 GB at its Q4_K_M build vs 571.6 GB for DeepSeek V4.1 Flash 552B's Q4_K_M. GLM-5.3-Flash 320B runs on more GPUs natively (8 vs 0).
- How much VRAM does DeepSeek V4.1 Flash 552B need vs GLM-5.3-Flash 320B?
- At 8k context, DeepSeek V4.1 Flash 552B needs approximately 571.6 GB of VRAM at its Q4_K_M build, while GLM-5.3-Flash 320B needs 218.5 GB at its Q4_K_M build. At the largest build each ships, DeepSeek V4.1 Flash 552B requires 1236.5 GB (FP16) vs 717.0 GB (FP16) for GLM-5.3-Flash 320B.
- Can you run DeepSeek V4.1 Flash 552B on the same GPUs as GLM-5.3-Flash 320B?
- 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 GLM-5.3-Flash 320B?
- DeepSeek V4.1 Flash 552B has 552B parameters (16B active, MoE) with a 1024k context window. GLM-5.3-Flash 320B has 320B parameters (18B active, MoE) with a 1024k context window.
- Which model fits in 24 GB of VRAM, DeepSeek V4.1 Flash 552B or GLM-5.3-Flash 320B?
- Neither fits in 24 GB: DeepSeek V4.1 Flash 552B needs 571.6 GB at Q4_K_M and GLM-5.3-Flash 320B needs 218.5 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 GLM-5.3-Flash 320B?
- At the full 1,048,576-token window both models support, V4.1 Flash's KV cache is 2.3 GB against GLM-5.3-Flash's 23.6 GB, roughly a 10x gap, even though GLM-5.3-Flash already caches only 11 of its 45 layers.