GLM-5.2 753B vs DeepSeek V4 Pro 1.6T
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
GLM-5.2 753B is more hardware-efficient: it needs 515.1 GB at its Q4_K_M build vs 1091.4 GB for DeepSeek V4 Pro 1.6T's Q4_K_M, fitting on 2 GPUs natively.
VRAM at each quantization (8k context)
FP32
GLM-5.2 753B
3374.9 GB
DeepSeek V4 Pro 1.6T
7168.1 GB
BF16
GLM-5.2 753B
1688.2 GB
DeepSeek V4 Pro 1.6T
3584.1 GB
FP16
GLM-5.2 753B
1688.2 GB
DeepSeek V4 Pro 1.6T
3584.1 GB
Q8_0
GLM-5.2 753B
898.0 GB
DeepSeek V4 Pro 1.6T
1905.0 GB
Q6_K
GLM-5.2 753B
693.9 GB
DeepSeek V4 Pro 1.6T
1471.3 GB
Q5_K_M
GLM-5.2 753B
601.9 GB
DeepSeek V4 Pro 1.6T
1276.0 GB
Q4_K_M
GLM-5.2 753B
515.1 GB
DeepSeek V4 Pro 1.6T
1091.4 GB
Q3_K_M
GLM-5.2 753B
407.1 GB
DeepSeek V4 Pro 1.6T
862.1 GB
Q2_K
GLM-5.2 753B
322.8 GB
DeepSeek V4 Pro 1.6T
682.9 GB
NVFP4
GLM-5.2 753B
423.1 GB
DeepSeek V4 Pro 1.6T
896.1 GB
| Quant | GLM-5.2 753B | DeepSeek V4 Pro 1.6T | Diff |
|---|---|---|---|
| FP32 | 3374.9 GB | 7168.1 GB | -53% |
| BF16 | 1688.2 GB | 3584.1 GB | -53% |
| FP16 | 1688.2 GB | 3584.1 GB | -53% |
| Q8_0 | 898.0 GB | 1905.0 GB | -53% |
| Q6_K | 693.9 GB | 1471.3 GB | -53% |
| Q5_K_M | 601.9 GB | 1276.0 GB | -53% |
| Q4_K_M | 515.1 GB | 1091.4 GB | -53% |
| Q3_K_M | 407.1 GB | 862.1 GB | -53% |
| Q2_K | 322.8 GB | 682.9 GB | -53% |
| NVFP4 | 423.1 GB | 896.1 GB | -53% |
Diff is GLM-5.2 753B relative to DeepSeek V4 Pro 1.6T. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | GLM-5.2 753B | DeepSeek V4 Pro 1.6T |
|---|---|---|
| Org | Z.ai | DeepSeek |
| Parameters | 753B | 1600B |
| Architecture | MoE (40B active) | MoE (49B active) |
| Context | 1024k tokens | 1024k tokens |
| Modalities | text | text, vision, video |
| License | MIT | MIT |
| Commercial | Yes | Yes |
| Released | 2026-06-13 | 2026-04-24 |
| GPUs (native) | 2 / 119 | 0 / 119 |
Benchmark scores
| Benchmark | GLM-5.2 753B | DeepSeek V4 Pro 1.6T |
|---|---|---|
| MMLU-Pro | 80.6 | 87.5 |
| GPQA Diamond | 91.2 | 90.1 |
| SWE-bench Pro | 62.1 | N/A |
| Terminal-Bench 2.1 | 81.0 | 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 GLM-5.2 753B(2)
- Apple M5 Ultra (512GB)512 GB
- Apple M3 Ultra (512GB)512 GB
GPUs that run only DeepSeek V4 Pro 1.6T(0)
Every GPU that runs DeepSeek V4 Pro 1.6T also runs GLM-5.2 753B.
Which should you use?
Choose GLM-5.2 753B if:
- • You have limited VRAM: it's a smaller model needing 515.1 GB vs 1091.4 GB
- • You're running coding tasks
- • You need chain-of-thought reasoning
- • It's the newer release (2026-06-13 vs 2026-04-24); check the benchmark table above for what actually improved
Choose DeepSeek V4 Pro 1.6T if:
- • You want maximum capability and have a 1092 GB+ GPU
- • Benchmark quality matters: scores 87.5 vs 80.6 on MMLU-Pro
- • You need vision/image understanding
Frequently asked questions
- Which is better, GLM-5.2 753B or DeepSeek V4 Pro 1.6T?
- GLM-5.2 753B has 753B parameters vs 1600B for DeepSeek V4 Pro 1.6T, so DeepSeek V4 Pro 1.6T is the larger model. GLM-5.2 753B is more hardware-efficient, needing 515.1 GB at its Q4_K_M build vs 1091.4 GB for DeepSeek V4 Pro 1.6T's Q4_K_M. GLM-5.2 753B runs on more GPUs natively (2 vs 0). On MMLU-Pro, DeepSeek V4 Pro 1.6T scores higher (87.5 vs 80.6).
- How much VRAM does GLM-5.2 753B need vs DeepSeek V4 Pro 1.6T?
- At 8k context, GLM-5.2 753B needs approximately 515.1 GB of VRAM at its Q4_K_M build, while DeepSeek V4 Pro 1.6T needs 1091.4 GB at its Q4_K_M build. At the largest build each ships, GLM-5.2 753B requires 1688.2 GB (FP16) vs 3584.1 GB (FP16) for DeepSeek V4 Pro 1.6T.
- Can you run GLM-5.2 753B on the same GPUs as DeepSeek V4 Pro 1.6T?
- These models have very different VRAM requirements, so they do not share the same compatible GPU set.
- What is the difference between GLM-5.2 753B and DeepSeek V4 Pro 1.6T?
- GLM-5.2 753B has 753B parameters (40B active, MoE) with a 1024k context window. DeepSeek V4 Pro 1.6T has 1600B parameters (49B active, MoE) with a 1024k context window.
- Which model fits in 24 GB of VRAM, GLM-5.2 753B or DeepSeek V4 Pro 1.6T?
- Neither fits in 24 GB: GLM-5.2 753B needs 515.1 GB at Q4_K_M and DeepSeek V4 Pro 1.6T needs 1091.4 GB at Q4_K_M. Both require a multi-GPU server with 1092 GB+ of combined VRAM.