granite-4.0-h-tiny
📣 Update [10-07-2025]: Added a default system prompt to the chat template to guide the model towards more professional, accurate, and safe responses.
Params
6.9 B
Context
131,072
Downloads 30d
292 K
Likes
206
Download history
daily snapshots · 10 days292 K278 K
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 | bf16 | 13.9 GB | 16.8 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 13.9 GB | 32.4 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/granite-4-0-h-tiny
{
"hf_id": "ibm-granite/granite-4.0-h-tiny",
"params_b": 6.94,
"context_length": 131072,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 291998,
"vram_estimates": [
{ "quant": "bf16", "gb": 16.8 }
],
"updated_at": "2026-07-28T18:06:54Z"
}
Specifications
- Architecture
- GraniteMoeHybridForCausalLM
- Parameters
- 6.9 B
- Tensor type
- BF16
- Context length
- 131,072
- Vocabulary
- 100,352
- Layers / heads
- 40 / 12
- Licence
- apache-2.0
- First seen on the Hub
- 2025-09-16
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with
Sponsored · GPU cloud
Not enough VRAM?
Spin up a 24 GB L4 instance in 40 seconds. $0.44/hr.