MiniMax-M2.1
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Params
228.7 B
Context
196,608
Downloads 30d
12 K
Likes
1,374
Download history
tracking started — chart appears after 7 days of snapshots (5 recorded)12 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 | f8_e4m3 | 230.1 GB | 288.0 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 192K ctx | 230.1 GB | 1,076.9 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/minimax-m2-1
{
"hf_id": "MiniMaxAI/MiniMax-M2.1",
"params_b": 228.69,
"context_length": 196608,
"license": { "id": "other", "commercial": "unknown" },
"downloads_30d": 11542,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 288.0 }
],
"updated_at": "2026-10-19T06:00:10Z"
}
Use via API
via OpenRouter · USD per 1M tokens · synced 2026-10-24$0.30
input / 1M
$1.20
output / 1M
$0.03
cached input / 1M
$1.50
1M in + 1M out
- Context window
- 204,800 tokens
- Max output
- 131,072 tokens
- Providers
- 1
- Cheapest provider
- Minimax · $0.30 / $1.20
- Best throughput
- —
- AA Intelligence / Coding / Agentic
- 20.9 / — / —
✓ Tool calling
✓ Reasoning
✓ Structured outputs
✗ Image input
✗ File input
✗ Audio input
✓ Prompt caching
Specifications
- Architecture
- MiniMaxM2ForCausalLM
- Parameters
- 228.7 B
- Tensor type
- F8_E4M3
- Context length
- 196,608
- Vocabulary
- 200,064
- Layers / heads
- 62 / 48
- Licence
- other
- First seen on the Hub
- 2025-12-20
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-20
Compare with any text-generation model