sarashina2.2-0.5b-instruct-v0.1
Model Elyza-tasks-100 Japanese MT Bench English MT Bench ------------------------------------------------------------------------------------------------- --------------- ----------------- ---------------- Qwen/Qwen2.5-0.5B-instruct 1.53 2.95 4.98 sarashina2.2-0.5B-instruct-v0.1 2.38 4.55 5.09 Rakuten/RakutenAI-2.0-mini-instruct 2.41 4.49 5.13 SakanaAI/TinySwallow-1.5B-Instruct 2.81 5.24 6.31 Qwen/Qwen2.5-1.5B-instru...
Params
790 M
Context
8,192
Downloads 30d
248 K
Likes
16
Download history
daily snapshots · 11 days251 K220 K
Sep 11Sep 14Sep 18Sep 21
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 | 1.6 GB | 2.4 GB | ✅ Runs comfortably |
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/sarashina2-2-0-5b-instruct-v0-1
{
"hf_id": "sbintuitions/sarashina2.2-0.5b-instruct-v0.1",
"params_b": 0.79,
"context_length": 8192,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 247967,
"vram_estimates": [
{ "quant": "bf16", "gb": 2.4 }
],
"updated_at": "2026-09-11T01:00:41Z"
}
Specifications
- Architecture
- LlamaForCausalLM
- Parameters
- 790 M
- Tensor type
- BF16
- Context length
- 8,192
- Vocabulary
- 102,400
- Layers / heads
- 24 / 16
- Licence
- mit
- First seen on the Hub
- 2025-02-26
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-11
Compare with any text-generation model