The independent standard for
open-weight AI

Objective composite scoring and rankings for 1000 models across benchmarks, efficiency, and community usage.

1000 Models Ranked
5 Benchmarks
5 Dimensions
Free Forever
Rank Model Score Tier Embed Change Compare
🥇
prism-ml
Ternary-Bonsai-27B-gguf
88.4 A 0
🥈
zai-org
GLM-5.2
87.3 A 0
🥉
prism-ml
Bonsai-27B-gguf
86.8 A 0
#4
prism-ml
Ternary-Bonsai-8B-gguf
3-13B
86.8 A 0
#5
deepseek-ai
DeepSeek-V4-Pro
86.2 A 0
#6
prism-ml
Bonsai-8B-gguf
3-13B
85.0 A 0
#7
Nanbeige
Nanbeige4.2-3B
3-13B
84.8 A 0
#8
deepseek-ai
DeepSeek-V4-Flash
84.3 A 0
#9
zai-org
GLM-5
83.5 A 0
#10
zai-org
GLM-5.1
83.4 A 0
#11
nvidia
NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4
83.3 A 0
#12
nvidia
NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
83.1 A 0
#13
internlm
internlm2_5-7b-chat
3-13B
83.1 A 0
#14
upstage
Solar-Open2-250B
83.0 A 0
#15
tencent
Hy3-preview
82.7 A 0
#16
zai-org
GLM-4.7
82.4 A 0
#17
deepseek-ai
DeepSeek-V3.2
82.4 A 0
#18
stepfun-ai
Step-3.5-Flash
82.2 A 0
#19
zai-org
GLM-5-FP8
82.0 A 0
#20
deepseek-ai
DeepSeek-V3.1
81.8 A 0
#21
zai-org
GLM-4.5
81.7 A 0
#22
moonshotai
Kimi-K2-Thinking
81.4 A 0
#23
MiniMaxAI
MiniMax-M2.5
80.8 A 0
#24
nvidia
NVIDIA-Nemotron-3-Super-120B-A12B-BF16
80.5 A 0
#25
XiaomiMiMo
MiMo-V2-Flash
80.5 A 0
#26
zai-org
GLM-5.1-FP8
80.2 A 0
#27
deepseek-ai
DeepSeek-V3-0324
80.2 A 0
#28
deepseek-ai
DeepSeek-R1-0528
80.1 A 0
#29
Qwen
Qwen3-235B-A22B-Instruct-2507
80.1 A 0
#30
MiniMaxAI
MiniMax-M2
80.0 A 0
#31
ByteDance-Seed
Seed-OSS-36B-Instruct
79.8 B 0
#32
meituan-longcat
LongCat-Flash-Chat
79.7 B 0
#33
moonshotai
Kimi-K2-Instruct
79.4 B 0
#34
deepseek-ai
DeepSeek-R1
78.3 B 0
#35
nvidia
NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4
77.7 B 0
#36
WeiboAI
VibeThinker-3B
3-13B
77.5 B 0
#37
nvidia
NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
76.9 B 0
#38
Qwen
Qwen3-30B-A3B-Thinking-2507
76.6 B 0
#39
openai
gpt-oss-120b
76.5 B 0
#40
nvidia
NVIDIA-Nemotron-3-Super-120B-A12B-FP8
76.0 B 0
#41
zai-org
GLM-4.7-Flash
76.0 B 0
#42
zai-org
GLM-4.5-Air
75.9 B 0
#43
nvidia
NVIDIA-Nemotron-3-Nano-30B-A3B-FP8
75.3 B 0
#44
nvidia
Nemotron-Cascade-2-30B-A3B
75.3 B 0
#45
XiaomiMiMo
MiMo-V2.5-Pro
73.8 B 0
#46
meta-llama
Llama-3.1-405B
73.7 B 0
#47
Qwen
Qwen3-Next-80B-A3B-Instruct
73.6 B 0
#48
Qwen
Qwen3-Next-80B-A3B-Thinking
73.2 B 0
#49
microsoft
phi-4
72.9 B 0
#50
Qwen
Qwen3-30B-A3B-Instruct-2507
72.3 B 0
#51
Qwen
QwQ-32B
71.1 B 0
#52
prism-ml
Bonsai-1.7B-gguf
<3B Edge
71.0 B 0
#53
Qwen
Qwen3-4B-Thinking-2507
3-13B
70.9 B 0
#54
Qwen
Qwen3-4B-Instruct-2507
3-13B
70.8 B 0
#55
Qwen
Qwen3-235B-A22B
70.2 B 0
#56
Qwen
Qwen2.5-32B
70.1 B 0
#57
deepseek-ai
DeepSeek-V3
70.0 B 0
#58
openai
gpt-oss-20b
69.8 C 0
#59
meta-llama
Llama-3.3-70B-Instruct
69.0 C 0
#60
tencent
Hunyuan-A13B-Instruct
68.8 C 0
#61
nvidia
NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16
67.3 C 0
#62
microsoft
Phi-3.5-mini-instruct
3-13B
67.2 C 0
#63
Qwen
Qwen2-72B-Instruct
66.8 C 0
#64
Qwen
Qwen2.5-14B
66.6 C 0
#65
meta-llama
Llama-3.1-70B-Instruct
66.6 C 0
#66
microsoft
Phi-3-mini-4k-instruct
3-13B
66.0 C 0
#67
Qwen
Qwen3-30B-A3B-Base
64.8 C 0
#68
XiaomiMiMo
MiMo-7B-RL
3-13B
63.9 C 0
#69
ibm-granite
granite-4.1-8b
3-13B
63.5 C 0
#70
LGAI-EXAONE
EXAONE-3.5-32B-Instruct
62.7 C 0
#71
internlm
internlm3-8b-instruct
3-13B
62.7 C 0
#72
meta-llama
Meta-Llama-3-70B-Instruct
61.6 C 0
#73
microsoft
Phi-4-mini-instruct
3-13B
61.2 C 0
#74
Qwen
Qwen2-7B
3-13B
60.2 C 0
#75
meta-llama
Meta-Llama-3-70B
59.1 D 0
#76
ibm-granite
granite-4.1-3b
3-13B
58.3 D 0
#77
meta-llama
Llama-3.1-70B
58.2 D 0
#78
meta-llama
Llama-3.1-8B-Instruct
3-13B
58.2 D 0
#79
LiquidAI
LFM2.5-8B-A1B
3-13B
57.9 D 0
#80
Qwen
Qwen2-7B-Instruct
3-13B
56.3 D 0
#81
LGAI-EXAONE
EXAONE-3.5-7.8B-Instruct
3-13B
55.0 D 0
#82
microsoft
Phi-3-mini-128k-instruct
3-13B
54.7 D 0
#83
Qwen
Qwen2.5-7B
3-13B
54.5 D 0
#84
Qwen
Qwen2.5-3B
3-13B
54.2 D 0
#85
google
gemma-2-9b
3-13B
54.1 D 0
#86
LiquidAI
LFM2.5-1.2B-Instruct
<3B Edge
53.0 D 0
#87
meta-llama
Meta-Llama-3-8B-Instruct
3-13B
52.7 D 0
#88
deepseek-ai
DeepSeek-Coder-V2-Lite-Instruct
Code
52.0 D 0
#89
XiaomiMiMo
MiMo-7B-Base
3-13B
51.6 D 0
#90
ibm-granite
granite-3.1-8b-instruct
3-13B
50.8 D 0
#91
LGAI-EXAONE
EXAONE-3.5-2.4B-Instruct
<3B Edge
50.8 D 0
#92
meta-llama
Llama-3.1-8B
3-13B
49.3 D 0
#93
meta-llama
Meta-Llama-3-8B
3-13B
48.8 D 0
#94
GSAI-ML
LLaDA-8B-Instruct
3-13B
48.6 D 0
#95
google
gemma-2-27b-it
47.2 D 0
#96
Qwen
Qwen2.5-1.5B
<3B Edge
47.2 D 0
#97
google
gemma-7b
3-13B
46.5 D 0
#98
HuggingFaceH4
zephyr-7b-beta
3-13B
46.1 D 0
#99
mistralai
Mistral-7B-Instruct-v0.2
3-13B
45.4 D 0
#100
google
gemma-2-9b-it
3-13B
45.2 D 0

Methodology

A transparent, reproducible scoring system that looks beyond simple benchmarks to capture the full picture of a model's utility.

🧠

Benchmarks

70% WEIGHT

Aggregated scores from MMLU-Pro, GPQA, HLE, GSM8K, and HumanEval. Adjusted for model contamination.

Efficiency

5% WEIGHT

Throughput (tokens/sec), memory footprint, and param-to-performance ratio on standard hardware.

🔥

Community

10% WEIGHT

Downloads, likes, and trending rank across the HuggingFace ecosystem.

🕐

Recency

15% WEIGHT

180-day half-life decay since last update. Rewards actively maintained models.

Reproducibility

0% WEIGHT

Open weights, reproducible evaluation code, and clear licensing (MIT/Apache preferred). Reserved for future weighting.

Why trust ModelRank?

  • Open Source

    MIT licensed and fully auditable methodology.

  • No Conflicts of Interest

    We don't train or host models. Independent evaluation only.

  • Reproducible

    All evaluation data is sourced from public HuggingFace APIs.

  • Updated Daily

    Fully automated via GitHub Actions cron jobs.

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