Model
Model explorer

LLaMA 7B

OPEN
Meta · LLaMA family · released Feb 24, 2023

Smallest first-gen LLaMA, trained on roughly 1T tokens for efficient research use under a gated non-commercial license.

ReasoningCodingVisionFunction callingTool useAgentic
-180.9
Elo · rank #421
Parameters
6.7B
Active params
6.7B (dense)
Context
2K tokens
Architecture
Dense decoder-only Transformer
License
LLaMA Non-Commercial Research License (gated application access)
Languages
API price (in/out)
No hosted API
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
AGIEvalReasoning23.9%#41
best: OLMo 3-Think 32B · 88.2%
ARC-ChallengeReasoning47.6%#130
best: Llama 3.1 405B · 96.9%
ARC-EasyReasoning72.8%#42
best: Phi-3-medium (14B) · 97.7%
BIG-Bench HardReasoning30.3%#132
best: ERNIE 4.5 300B-A47B · 94.3%
GSM8KMath11.0%#177
best: Llama 3.1 405B · 96.8%
HellaSwagReasoning76.1%#108
best: Claude 3 Opus · 95.4%
best: Gorilla 7B · 71.7%
HumanEvalCoding10.5%#182
best: Claude Opus 4.5 · 99.4%
MATH-500Math2.9%#202
best: GPT-5 · 99.4%
MBPPCoding17.7%#107
best: Llama-3.3-Nemotron-Super-49B v1 (Reasoning On) · 91.3%
MMLUKnowledge35.1%#263
best: OpenAI o3 · 92.9%
OpenBookQAReasoning57.2%#17
best: Claude 1 · 90.8%
PIQAReasoning79.8%#47
best: GPT-4o mini · 93.1%
RACE-HReasoning46.9%#16
best: Claude 3 Opus · 92.9%
Social IQaReasoning48.9%#29
best: Apple DCLM-Baseline 7B · 82.9%
best: Gorilla 7B · 83.8%
best: Gorilla 7B · 59.1%
TriviaQAKnowledge50.0%#43
best: Sarvam-1 (2B) · 90.6%
TruthfulQAKnowledge27.4%#106
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
WinoGrandeReasoning70.1%#103
best: PaLM 2 · 90.9%
Run it locally
VRAM @ Q4
6.6 GB
VRAM @ FP16
13.5 GB
Fits on (Q4)
RTX 3060 12GBRTX 4070 Ti 16GBRTX 3090 24GBRTX 4090 24GBRTX 5090 32GBM4 Pro 48GBM3 Max 128GBM3 Ultra 512GBA100 80GBH100 80GBH200 141GBB200 192GB
No verifiably-sourced LLaMA-1-7B-specific RTX 4090 llama.cpp benchmark was found; do not conflate with unrelated Llama-3/Mistral 7B figures circulating online.
Quantizations
GGUF · GPTQ · AWQ · GGML
API price weights · each benchmark row carries its own source badge (see methodology)