TinyLlama / text-generation updated 2 years ago

TinyLlama-1.1B-Chat-v1.0

Name: TinyLlama-1.1B-Chat-v1.0
Author: TinyLlama

The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-09-01.

Params

1.1 B

Context

2,048

Downloads 30d

2.5 M

Likes

1,715

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

2.6 M2.5 M

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	2.2 GB	3.1 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 · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/tinyllama-1-1b-chat-v1-0
{
  "hf_id": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
  "params_b": 1.10,
  "context_length": 2048,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 2542599,
  "vram_estimates": [
    { "quant": "bf16", "gb": 3.1 }
  ],
  "updated_at": "2026-07-28T17:07:40Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: LlamaForCausalLM
Parameters: 1.1 B
Tensor type: BF16
Context length: 2,048
Vocabulary: 32,000
Layers / heads: 22 / 32
Licence: apache-2.0
First seen on the Hub: 2023-12-30
Training datasets: cerebras/SlimPajama-627B, bigcode/starcoderdata, HuggingFaceH4/ultrachat_200k, HuggingFaceH4/ultrafeedback_binarized
Added to our catalog: 2026-07-28

Compare with

Qwen3-0.6B 29.7 M Qwen2.5-1.5B-Instruct 14.0 M Llama-3.2-1B-Instruct 10.4 M Qwen3-1.7B 7.8 M Qwen2.5-0.5B-Instruct 6.6 M gemma-3-1b-it 4.7 M

Appears in

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