Seed OSS 36B Base — Hardware Requirements & GPU Compatibility
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Seed OSS 36B Base is a 36.2B-parameter open language model from ByteDance-Seed in the Seed-OSS family. It supports a context window of up to 524,288 tokens. At Q4_K_M it needs about 22.26 GB of VRAM — see which GPUs and Macs can run it below.
1.7K downloads
62 likesSpecifications
- Publisher
- ByteDance-Seed
- Family
- Seed-OSS
- Parameters
- 36.2B
- Architecture
- SeedOssForCausalLM
- Context Length
- 524,288 tokens
- Vocabulary Size
- 155,136
- Release Date
- 2025-08-20
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Seed OSS 36B Base Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 15.9 GB | 84.4 GB | 15.36 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 18.2 GB | 86.6 GB | 17.62 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 22.3 GB | 90.7 GB | 21.69 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 26.3 GB | 94.8 GB | 25.76 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 30.4 GB | 98.8 GB | 29.82 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 36.7 GB | 105.2 GB | 36.15 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 72.9 GB | 141.3 GB | 72.30 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Seed OSS 36B Base?
Q4_K_M · 22.3 GBSeed OSS 36B Base (Q4_K_M) requires 22.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 29+ GB is recommended. Using the full 524K context window can add up to 68.4 GB, bringing total usage to 90.7 GB. 5 GPUs can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Which Devices Can Run Seed OSS 36B Base?
Q4_K_M · 22.3 GB21 devices with unified memory can run Seed OSS 36B Base, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Seed OSS 36B Base need?
Seed OSS 36B Base requires 22.3 GB of VRAM at Q4_K_M, or 72.9 GB at BF16. Full 524K context adds up to 68.4 GB (90.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 36.2B × 4.8 bits ÷ 8 = 21.7 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 69 GB (at full 524K context)
VRAM usage by quantization
Q4_K_M22.3 GBQ4_K_M + full context90.7 GB- Can NVIDIA GeForce RTX 4090 run Seed OSS 36B Base?
Yes, at Q4_K_M (22.3 GB) or lower. Higher quantizations like Q5_K_M (26.3 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Seed OSS 36B Base?
For Seed OSS 36B Base, Q4_K_M (22.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (26.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 15.9 GB.
VRAM requirement by quantization
Q2_K15.9 GBQ4_K_M ★22.3 GBQ5_K_M26.3 GBQ6_K30.4 GBQ8_036.7 GBBF1672.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Seed OSS 36B Base on a Mac?
Seed OSS 36B Base requires at least 15.9 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Seed OSS 36B Base locally?
Yes — Seed OSS 36B Base can run locally on consumer hardware. At Q4_K_M quantization it needs 22.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Seed OSS 36B Base?
At Q4_K_M, Seed OSS 36B Base can reach ~131 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~29 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 22.3 × 0.55 = ~131 tok/s
Estimated speed at Q4_K_M (22.3 GB)
~131 tok/s~29 tok/s~98 tok/s~81 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Seed OSS 36B Base?
At Q4_K_M, the download is about 21.69 GB. The full-precision BF16 version is 72.30 GB. The smallest option (Q2_K) is 15.36 GB.
- Which GPUs can run Seed OSS 36B Base?
5 consumer GPUs can run Seed OSS 36B Base at Q4_K_M (22.3 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090.
- Which devices can run Seed OSS 36B Base?
21 devices with unified memory can run Seed OSS 36B Base at Q4_K_M (22.3 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.