DeepSeek-V3
We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient inference and cost-effective training, DeepSeek-V3 adopts Multi-head Latent Attention (MLA) and DeepSeekMoE architectures, which were thoroughly validated in DeepSeek-V2. Furthermore, DeepSeek-V3 pioneers an auxiliary-loss-free strategy for load balancing and sets...
Params
684.5 B
Context
163,840
Downloads 30d
1.2 M
Likes
4,169
Download history
daily snapshots · 10 days1.2 M1.2 M
Jul 28Jul 31Aug 3Aug 6
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f8_e4m3 | 688.6 GB | 860.6 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 160K ctx | 688.6 GB | 2,811.5 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ curl -s https://aimodelscomparison.com/api/v1/models/deepseek-v3
{
"hf_id": "deepseek-ai/DeepSeek-V3",
"params_b": 684.53,
"context_length": 163840,
"license": { "id": "", "commercial": "unknown" },
"downloads_30d": 1211587,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 860.6 }
],
"updated_at": "2026-07-28T18:03:33Z"
}
Specifications
- Architecture
- DeepseekV3ForCausalLM
- Parameters
- 684.5 B
- Tensor type
- F8_E4M3
- Context length
- 163,840
- Vocabulary
- 129,280
- Layers / heads
- 61 / 128
- First seen on the Hub
- 2024-12-25
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
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