Model
Model explorer
Phi-3-small (7B)
OPENMicrosoft · Phi-3 family · released May 21, 2024
7B dense mid-tier Phi-3 with blocksparse attention; 8K (also 128K variant), 75.7 MMLU.
ReasoningCodingVisionFunction callingTool useAgentic
658.0
Elo · rank #274
Parameters
7B
Active params
7B (dense)
Context
8K tokens
Architecture
Dense decoder-only Transformer (alternating dense + blocksparse attention)
License
MIT
Languages
—
API price (in/out)
$0.15 / $0.6
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
best: OLMo 3-Think 32B · 88.2%
best: this model · 58.1%
best: Llama 3.1 405B · 96.9%
best: Phi-3-medium (14B) · 97.7%
best: ERNIE 4.5 300B-A47B · 94.3%
best: GPT-5.6 · 94.6%
best: Llama 3.1 405B · 96.8%
best: Claude 3 Opus · 95.4%
best: Claude Opus 4.5 · 99.4%
best: LG EXAONE 3.0 7.8B Instruct · 8.92
best: GPT-5 · 99.4%
best: Llama-3.3-Nemotron-Super-49B v1 (Reasoning On) · 91.3%
best: OpenAI o3 · 92.9%
best: Hunyuan-Large (A52B) · 9.4
best: Claude 1 · 90.8%
best: GPT-4o mini · 93.1%
best: Apple DCLM-Baseline 7B · 82.9%
best: Sarvam-1 (2B) · 90.6%
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
best: PaLM 2 · 90.9%
Run it locally
VRAM @ Q4
6 GB
VRAM @ FP16
15 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
Throughput data unavailable.
Quantizations
GGUF Q4 · ONNX INT4
Phi-3 family
Elo progression across releases
API price $0.15/$0.6 · each benchmark row carries its own source badge (see methodology)