Motif-3
Motif 3 is a large-scale, decoder-only Mixture-of-Experts (MoE) language model with 314 billion total parameters and 13.2 billion parameters activated per token. It is built from the ground up by Motif Technologies following a fully in-house, proprietary design.
Params
314.8 B
Context
262,144
Downloads 30d
2 K
Likes
155
Download history
tracking started — chart appears after 7 days of snapshots (0 recorded)2 K downloads in the last 30 days
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 | bf16 | 629.7 GB | 740.4 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 256K ctx | 629.7 GB | 2,204.4 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/motif-3
{
"hf_id": "Motif-Technologies/Motif-3",
"params_b": 314.84,
"context_length": 262144,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 2370,
"vram_estimates": [
{ "quant": "bf16", "gb": 740.4 }
],
"updated_at": "2026-11-11T06:00:04Z"
}
Use via API
via OpenRouter · USD per 1M tokens · synced 2026-11-11$0.30
input / 1M
$1.20
output / 1M
$0.06
cached input / 1M
$1.50
1M in + 1M out
- Context window
- 262,144 tokens
- Max output
- 235,929 tokens
- Providers
- 1
- Cheapest provider
- KT · $0.30 / $1.20
- Best throughput
- —
- AA Intelligence / Coding / Agentic
- — / 63.5 / 28.4
✗ Tool calling
✓ Reasoning
✓ Structured outputs
✗ Image input
✗ File input
✗ Audio input
✓ Prompt caching
Specifications
- Architecture
- MotifForCausalLM
- Parameters
- 314.8 B
- Tensor type
- BF16
- Context length
- 262,144
- Vocabulary
- 220,160
- Layers / heads
- 53 / 80
- Licence
- mit
- First seen on the Hub
- 2026-08-07
- Training datasets
- undisclosed
Compare with any text-generation model