sarvam-30b
1. Introduction 2. Architecture 3. Benchmarks - Knowledge & Coding - Reasoning & Math - Agentic 4. Inference - Hugging Face - vLLM - SGLang 5. Footnote 6. Citation
Params
32.2 B
Context
131,072
Downloads 30d
304 K
Likes
225
Download history
daily snapshots · 11 days304 K237 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 | f32 | 128.6 GB | 146.8 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 128.6 GB | 219.1 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/sarvam-30b
{
"hf_id": "sarvamai/sarvam-30b",
"params_b": 32.15,
"context_length": 131072,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 304336,
"vram_estimates": [
{ "quant": "f32", "gb": 146.8 }
],
"updated_at": "2026-09-11T01:00:33Z"
}
Specifications
- Architecture
- SarvamMoEForCausalLM
- Parameters
- 32.2 B
- Tensor type
- F32
- Context length
- 131,072
- Vocabulary
- 262,144
- Layers / heads
- 19 / 64
- Licence
- apache-2.0
- First seen on the Hub
- 2026-03-03
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-11
Compare with any text-generation model