Note: Overall leaderboard rankings may not reflect true model quality — individual benchmarks give a clearer picture. ARC-Challenge MMLU GPQA GSM8K Artificial Analysis Intelligence Index v4.1
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-(CoderPPL)

54 models

CoderPPL — a code perplexity (PPL) benchmark measuring how well a language model predicts real-world, hand-written code across 5 languages (Python, JavaScript, HTML, Lua, Shell) and diverse programming domains. Unlike natural-language PPL, code PPL tests syntax understanding, structural reasoning, and domain-specific patterns.

Top 5 Models Performance

Qwen: Qwen3.5 9B ################################## -1.6914
Qwen: qwen3.5-9b-base ################################### -1.7468
Qwen: Qwen3.5 4B #################################### -1.7894
Yandex: YandexGPT Lite 5 ######################################## -2
Qwen: Qwen3.5 2B ######################################## -2.0063
– 970 – 1.1T
– 2019 – 2026
Rank Model Score
🇨🇳 1 Qwen: Qwen3.5 9B通义千问 -1.6914
🇨🇳 2 Qwen: qwen3.5-9b-base通义千问 -1.7468
🇨🇳 3 Qwen: Qwen3.5 4B通义千问 -1.7894
🇷🇺 4 Yandex: YandexGPT Lite 5Яндекс -2
🇨🇳 5 Qwen: Qwen3.5 2B通义千问 -2.0063
❓ 6 LocoreMind: locooperator-4b -2.0148
🇨🇳 7 DeepSeek: deepseek-coder-1.3b-instruct深度求索 -2.0481
🇷🇺 8 T-Tech: t-lite-it-1.0 -2.08
🇫🇷 9 Mistral AI: ministral-3-3b-instruct-2512 -2.134
❓ 10 Houssem Fatnasssi: kilma-v1-base -2.1805
🇺🇸 11 NVIDIA Corporation: NVIDIA Nemotron 3 Nano 4B -2.1821
🇬🇧 12 Stability AI: stable-code-3b -2.1903
🇨🇳 13 Qwen: Qwen3 4B通义千问 -2.2233
❓ 14 huggingfacebio: carbon-x -2.259
🇨🇳 15 Qwen: Qwen3.5 0.8B通义千问 -2.313
🇺🇸 16 OpenAI: gpt-oss-20b -2.3451
🇺🇸 17 Microsoft: phi-4-mini-instruct -2.4022
🇨🇳 18 Qwen: qwen2-1.5b-instruct通义千问 -2.44
🇺🇸 19 Hugging Face Smol Models Research: smollm3-3b-base -2.4737
🇨🇳 20 Qwen: qwen3-0.6b-base通义千问 -2.5332
🇺🇸 21 IBM Granite: granite-4.1-3b -2.57
🇺🇸 22 Google: Gemma 4 E4B Instruct -2.6205
🇷🇺 23 MWS AI: cotype-nano -2.63
🇺🇸 24 NVIDIA Corporation: nvidia-nemotron-3.5-bolt-e4b -2.6951
🇺🇸 25 Meta Llama: Llama 3.2 3B Instruct -2.7202
🇺🇸 26 Hugging Face Smol Models Research: smollm3-3b -2.7254
🇺🇸 27 Hugging Face Smol Models Research: smollm2-360m -2.7327
🇨🇳 28 Qwen: qwen2.5-0.5b通义千问 -2.7341
❓ 29 state-spaces: mamba-1.4b -2.7518
🇺🇸 30 LiquidAI: lfm-3-1.7b -2.8166
❓ 31 atomicchat: lfm3-1.7b-uncensored -2.8779
🇨🇳 32 Qwen: qwen2.5-0.5b-instruct通义千问 -2.9416
🇨🇳 33 Qwen: Qwen3 0.6B通义千问 -2.9768
🇨🇳 34 OpenBMB: minicpm5-1b -2.9929
🇺🇸 35 LiquidAI: LFM2.5 1.2B Instruct -3.0582
🇦🇪 36 Technology Innovation Institute: falcon-h1-tiny-coder-90m -3.4801
🇺🇸 37 LiquidAI: lfm-2.5-8b-a1b -3.5556
🇷🇺 38 Sapbot: Grok 4 Distill SmolLM2 135M -3.6157
🇺🇸 39 LiquidAI: LFM2.5-230M -3.76
❓ 40 state-spaces: mamba-130m -3.8016
🇺🇸 41 Google: Gemma 4 E2B Instruct -3.8687
🇺🇸 42 OpenAI Community: GPT-2 -4.0491
🇺🇸 43 AMD: AMD-135m -4.0935
❓ 44 SupraLabs: Supra-1.5 Instruct EXP -5.75
❓ 45 SupraLabs: Supra-50M-Reasoning -5.76
🇫🇷 46 BigScience: bloom-560m -6.9102
🇨🇳 47 Tencent: youtu-llm-2b腾讯控股有限公司 -9.4946
🇺🇸 48 LiquidAI: lfm-2.5-350m -10.5455
❓ 49 raincandy-u: rain-100m -12.2946
❓ 50 pleias: baguettotron -19.0947
🇺🇸 51 NVIDIA Corporation: locateanything-3b -22.65
🇦🇪 52 Technology Innovation Institute: Falcon H1 Tiny 90M Instruct -24.67
🇷🇺 53 Sapbot: ToyLlama-50M -37.0286
❓ 54 Amir: tiny-llm -43.49689