Llama 3.2 3B Instruct
Meta AIhuggingface.co/meta-llama/Llama-3.2-3B-Instruct
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
Updated 12 min ago · first seen 11 Sept 2026
model_01M294WWNJ3JRF3C1RTJQJGGE0
- Parameters
- 3.21B
- T2 · 2 h ago
- Context
- 131.1K tokens
- T2 · 2 h ago
- Released
- 25 Sept 2024
- T2 · 2 h ago
- Knowledge cutoff
- Dec 2023
- T2 · 2 h ago
Specification
- Release date
- 25 Sept 2024
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Openness
- restricted
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium
- Parameters
- 3.21B
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium
- Context window
- 131.1K tokens
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Max output
- 118K tokens
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Knowledge cutoff
- Dec 2023
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Modalities
- text
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Input modalities
- text
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Output modalities
- text
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Tokenizer
- Llama3
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Hugging Face repo
- meta-llama/Llama-3.2-3B-Instruct
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Pipeline tag
- text-generation
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium
- Downloads
- 1,587,087
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 min agomedium
- Likes
- 2,559
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 min agomedium
- Instruct type
- llama3
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Last modified
- 2024-10-24T15:07:29+00:00
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium
- Openrouter id
- meta-llama/llama-3.2-3b-instruct
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Supported parameters
- frequency_penalty, logit_bias, logprobs, max_tokens, min_p, presence_penalty, repetition_penalty, seed, stop, structured_outputs, temperature, top_k, top_logprobs, top_p
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →
Provenance
Attributed facts
22
Source tiers
T222
Freshest observation
12 min ago
Conflicts
None
Modalities
- Modalities
- text
- Input
- text
- Output
- text
Capabilities
Tool calling
No
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Unavailable
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
- 131.1K tokens
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Max output
- 118K tokens
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Knowledge cutoff
- Dec 2023
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
- Tokenizer
- Llama3
Source:OpenRouter public model & pricing listingT2observed 2 h agomedium
No benchmark results recorded
Current prices
| Provider | Input / 1M | Output / 1M | Cached in | Batch in / out | Context | Observed | Source |
|---|---|---|---|---|---|---|---|
| OpenRoutermeta-llama/llama-3.2-3b-instruct | $0.05 | $0.33 | — | — | 131.1K | 27 min ago | openrouter.aiT2 |
USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.
Available through 1
Price history
Input price · USD / 1M tokens
Output price · USD / 1M tokens
- OpenRouter
Memory need = bytes per parameter (4-bit ≈ 0.5 × 1.15 overhead, 8-bit 1.0, fp16 2.0) + a KV-cache allowance. Not a measurement.
| Hardware | Quantization | Memory | Est. need | Fits |
|---|---|---|---|---|
| NVIDIA DGX B200 | 4bit | 1,440 GB | 2.4 GB | Yes |
| Apple M3 Ultra | 4bit | — | 2.4 GB | Yes |
| Mac Studio (Apple M5 Ultra) | 4bit | — | 2.4 GB | Yes |
| AMD Instinct MI325X | 4bit | 256 GB | 2.4 GB | Yes |
| AMD Instinct MI300X | 4bit | 192 GB | 2.4 GB | Yes |
| Apple M2 Ultra | 4bit | — | 2.4 GB | Yes |
| NVIDIA B200 | 4bit | 180 GB | 2.4 GB | Yes |
| NVIDIA H200 | 4bit | 141 GB | 2.4 GB | Yes |
| NVIDIA H200 NVL | 4bit | 141 GB | 2.4 GB | Yes |
| Apple M1 Ultra | 4bit | — | 2.4 GB | Yes |
| Apple M3 Max | 4bit | — | 2.4 GB | Yes |
| Apple M4 Max | 4bit | — | 2.4 GB | Yes |
| Mac Studio (Apple M5 Max) | 4bit | — | 2.4 GB | Yes |
| MacBook Pro (Apple M5 Max) | 4bit | — | 2.4 GB | Yes |
| NVIDIA DGX Spark | 4bit | 128 GB | 2.4 GB | Yes |
| Apple M2 Max | 4bit | — | 2.4 GB | Yes |
| NVIDIA H100 NVL | 4bit | 94 GB | 2.4 GB | Yes |
| NVIDIA A100 80GB | 4bit | 80 GB | 2.4 GB | Yes |
| NVIDIA H100 SXM | 4bit | 80 GB | 2.4 GB | Yes |
| Apple M1 Max | 4bit | — | 2.4 GB | Yes |
| Apple M4 Pro | 4bit | — | 2.4 GB | Yes |
| Mac mini (Apple M5 Pro) | 4bit | — | 2.4 GB | Yes |
| MacBook Pro (Apple M5 Pro) | 4bit | — | 2.4 GB | Yes |
| Apple M3 Pro | 4bit | — | 2.4 GB | Yes |
| Apple M1 Pro | 4bit | — | 2.4 GB | Yes |
| Apple M2 Pro | 4bit | — | 2.4 GB | Yes |
| Apple M4 | 4bit | — | 2.4 GB | Yes |
| iMac (Apple M4) | 4bit | — | 2.4 GB | Yes |
| Mac mini (Apple M6) | 4bit | — | 2.4 GB | Yes |
| MacBook Air (Apple M5) | 4bit | — | 2.4 GB | Yes |
| MacBook Pro (Apple M5) | 4bit | — | 2.4 GB | Yes |
| NVIDIA GeForce RTX 5090 | 4bit | 32 GB | 2.4 GB | Yes |
| Apple M2 | 4bit | — | 2.4 GB | Yes |
| Apple M3 | 4bit | — | 2.4 GB | Yes |
| NVIDIA GeForce RTX 3090 | 4bit | 24 GB | 2.4 GB | Yes |
| NVIDIA GeForce RTX 4090 | 4bit | 24 GB | 2.4 GB | Yes |
| Apple M1 | 4bit | — | 2.4 GB | Yes |
Ancestors 0
None recorded.
This model
Llama 3.2 3B Instruct
3.21B params
Quantizations 0
None recorded.
Descendants 14
- 3b-de-ft-research_release3.3B
- 3b-de-pretrain-research_release3.78B
- 3b-es_it-ft-research_release3.3B
- 3b-es_it-pretrain-research_release3.78B
- 3b-fr-ft-research_release3.3B
- 3b-fr-pretrain-research_release3.78B
- 3b-hi-ft-research_release3.3B
- 3b-ko-ft-research_release3.3B
- 3b-ko-pretrain-research_release3.78B
- 3b-zh-ft-research_release3.3B
- 3b-zh-pretrain-research_release3.78B
- orpheus-3b-0.1-ft3.78B
- orpheus-3b-0.1-pretrained3.78B
- 3b-hi-pretrain-research_release3.78B
Papers 0
No papers linked yet.
Repositories 0
No repositories linked yet.
As of
Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.
Claim history · Openness
Opennessopenness1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| restricted | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
OpenRouter lists Llama 3.2 3B Instruct at $0.05 in / $0.33 out per 1M tokens
openrouter
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/orpheus-3b-0.1-ft | model_page | T2· Quality secondary | 2 min ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/models?author=meta-llama&p=0&sort=downloads | listing | T2· Quality secondary | 12 min ago | 3 |
| OpenRouter public model & pricing listing | openrouter.ai/api/v1/models | catalogue | T2· Quality secondary | 27 min ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-zh-pretrain-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-ko-pretrain-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-de-pretrain-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-zh-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-fr-pretrain-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-ko-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-es_it-pretrain-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-es_it-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-fr-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-de-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/3b-hi-ft-research_release | model_page | T2· Quality secondary | 2 h ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/canopylabs/orpheus-3b-0.1-pretrained | model_page | T2· Quality secondary | 2 h ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.