v2.2 · 2026-06-12

TinyLlama 1.1B Chat v1.0

tinyllama-1-1b-chat-v1

TEXT-CHAT

TinyLlama 1.1B Chat v1.0 is a 1.1B text chat model profile for local AI planning. This page records provider, license, context, quantization, hardware-fit estimates, setup hints, source links, and caveats so readers do not choose a model by name alone.

PROVIDER

TinyLlama

FAMILY

TinyLlama

MODEL TYPE

text-chat

PARAMETERS

1.1B

MODALITIES

text

ARCHITECTURE

Llama-2-compatible decoder-only transformer chat model.

CONTEXT WINDOW

2,048 tokens

TRAINING TOKENS

3.0T

RELEASE DATE

—

LICENSE & LINKS

Apache-2.0license text

MODEL CARD

huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0

HUGGING FACE

TinyLlama/TinyLlama-1.1B-Chat-v1.0

GGUF REPOSITORIES

TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF community conversion

Community GGUF conversion with Q4_K_M, Q5_K_M and Q8_0 file listings and RAM estimates.

SETUP HINTS

OLLAMA

Run `ollama run tinyllama:1.1b-chat-q4_K_M`.

LM STUDIO

Use a TinyLlama 1.1B Chat GGUF and select Q4_K_M or Q8_0 depending on quality/memory preference.

LLAMA.CPP

Use a standard text GGUF loader with a 2048-token context, as shown in the GGUF repository examples.

QUANTIZATION FILE SIZES (GGUF)

Q4_K_M

0.67 GB

Q5_K_M

0.78 GB

Q8_0

1.17 GB

Quantization note: Q4_K_M for tiny local demos; Q8_0 if the goal is to preserve as much quality as possible because the file is still small.

RAM / VRAM ESTIMATES

MIN RAM

3.17 GB

COMFORTABLE RAM

6 GB

MIN VRAM

1 GB

COMFORTABLE VRAM

2 GB

These are conservative local-inference estimates, not official hardware requirements.

HARDWARE FIT

CPU only (no GPU)

yes

8 GB RAM

yes

16 GB RAM

yes

32 GB RAM

yes

8 GB VRAM

yes

12 GB VRAM

yes

24 GB VRAM

yes

Apple Silicon (unified memory)

yes

Hardware fit values are conservative local-inference estimates based on GGUF size plus runtime and KV-cache overhead. Actual requirements depend on context length, quantization, runtime, GPU offload, and other running apps.

BEST FOR

·Toy and educational chat demos

·Local stack smoke tests

·Very small edge-device experiments

·Simple classification templates where quality expectations are low

AVOID IF

·You need a genuinely capable assistant

·You need reliable summarization

·You need long context

·You need factual reliability

·You need tool use or structured reasoning

CAVEATS

·The exact chat checkpoint release date was not confirmed in cited sources from the permitted sources, so `releaseDate` is null.

·This is useful mainly for toy, demo, classroom and edge scenarios, not serious general chat.

·The cited GGUF is a community conversion.

·TheBloke's listed RAM figures assume no GPU offload and may differ from other runtimes.

·RAM and VRAM estimates are derived from GGUF/Ollama package size plus conservative overhead; KV cache, context length, batch size, runtime and GPU offload choices can materially change memory needs.

SOURCE URLS