The LLM benchmark aggregator.

Granite 4.0 H Small

IBM

Strongest in Factual grounding (#14 of 104), weakest in Human preference (#243 of 354). Above par in 6 of 9 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Claude 3 Opus and ahead of Kimi K2.6 and GPT-6 Sol.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Safety54.8−6.6#54/3272/3

Factual grounding62−8.7#14/1041/1

Toxicity avoidance58.4−0.6#17/2661/1

Harm refusal55.2−6.3#68/2901/2

Secure code54.5−11.7#117/2681/1

Jailbreak resistance53.3−11.7#139/2661/1

Fairness47.7−22.3#143/2901/2

Human preference45.8−23#243/3541/1

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Granite 4.0 H Small, left for the other.

OLMoE 1B-7B Instructwon 6 · lost 0

SmolLM 1.7B Instructwon 6 · lost 0

H2o Danube3 500M Chatwon 6 · lost 0

Laguna Xs 2.1won 6 · lost 0

RakutenAI 7B Instructwon 6 · lost 0

Falcon Mamba 7B Instructwon 6 · lost 0

GLM-4 9B Chatwon 6 · lost 0

Qwen2.5 0.5B Instructwon 6 · lost 0

Magistral Smallwon 6 · lost 0

Magistral Small 1.2won 6 · lost 0

Laguna S 2.1won 6 · lost 0

Falcon H1 0.5B Instructwon 6 · lost 0

Ling 3.0 Flash VLwon 6 · lost 0

Jamba 1.6 Miniwon 6 · lost 0

Mimo V2.6 Pro Ultraspeedwon 6 · lost 0

Phi-4 Mini Instructwon 6 · lost 0

Qwen2.5 3B Instructwon 6 · lost 0

Jamba 1.6 Largewon 6 · lost 0

Qwen2.5 1.5B Instructwon 6 · lost 0

Jamba Mini 1.7won 7 · lost 0

OLMo 7B Instructwon 8 · lost 0

SmolLM2 1.7B Instructwon 8 · lost 0

Zephyr 7B Betawon 8 · lost 0

Nous Hermes 2 Mixtral 8x7B DPOwon 8 · lost 0

DBRX Instructwon 8 · lost 0

Mixtral 8x7B Instructwon 8 · lost 0

GPT-3.5 Turbowon 8 · lost 0

Amazon Nova Microwon 8 · lost 1

Command R+won 8 · lost 1

Gemma 2B ITwon 7 · lost 1

Gemma 7B ITwon 7 · lost 1

Mistral 7B Instruct v0.2won 7 · lost 1

Granite 3.0 2B Instructwon 7 · lost 1

Llama 3.2 3B Instructwon 7 · lost 1

Starling LM 7B Betawon 7 · lost 1

Granite 3.0 8B Instructwon 7 · lost 1

DeepSeek LLM 67B Chatwon 7 · lost 1

Qwen1.5 14B Chatwon 7 · lost 1

Phi-3 Medium 4K Instructwon 7 · lost 1

Llama 3 8B Instructwon 7 · lost 1

Mixtral 8x22B Instructwon 7 · lost 1

Jamba 1.5 Miniwon 7 · lost 1

Gemma 2 9B ITwon 7 · lost 1

Jamba Large 1.7won 6 · lost 1

Qwen3 8Bwon 6 · lost 1

Mistral Instruct v0.1 (7B)won 5 · lost 1

RakutenAI 7B Chatwon 5 · lost 1

PowerMoE 3Bwon 5 · lost 1

Phi 2won 5 · lost 1

PowerLM 3Bwon 5 · lost 1

LFM2 350Mwon 5 · lost 1

SmolLM2 360M Instructwon 5 · lost 1

CodeLlama 7B Instructwon 5 · lost 1

Qwen2 7B Instructwon 5 · lost 1

OLMo 2 7B Instructwon 5 · lost 1

Aya 23 8Bwon 5 · lost 1

SEA LION V1 7B ITwon 5 · lost 1

Grok Build 0.1won 5 · lost 1

DeepSeek R1 Distill Qwen 7Bwon 5 · lost 1

DeepSeek R1 Distill Llama 8Bwon 5 · lost 1

H2o Danube3 4B Chatwon 5 · lost 1

Command R7Bwon 5 · lost 1

LFM2 700Mwon 5 · lost 1

NexusRaven V2 13Bwon 5 · lost 1

Ling 3.0 Flashwon 5 · lost 1

SmolLM 360M Instructwon 5 · lost 1

Granite 3.2 8B Instructwon 5 · lost 1

Open Codestral Mambawon 5 · lost 1

Aya 23 35Bwon 5 · lost 1

LFM2 1.2Bwon 5 · lost 1

Granite 3.0 1B A400M Instructwon 5 · lost 1

Gemma 4 E2Bwon 5 · lost 1

Jamba Instructwon 5 · lost 1

Yi 1.5 9B Chatwon 5 · lost 1

Sarvam 1won 5 · lost 1

Gemma 4 E4Bwon 5 · lost 1

SeaLLMs V3 7B Chatwon 5 · lost 1

Komodo 7B Basewon 5 · lost 1

WizardLM 2.8x22Bwon 5 · lost 1

Kimi K2.7 Codewon 5 · lost 1

IBM Granite 4.0 Microwon 5 · lost 1

Gemma 4 12Bwon 5 · lost 1

Gemma2 9B Cpt Sea Lionv3 Instructwon 5 · lost 1

Qwen2.5 32B Instructwon 5 · lost 1

LongWriter Glm4 9Bwon 5 · lost 1

Qwen2.5 14B Instruct 1Mwon 5 · lost 1

GLM-5 Turbowon 5 · lost 1

Qwen 2.5 Instruct (7B)won 5 · lost 1

Sarvam 30Bwon 5 · lost 1

Qwen2.5 14B Instructwon 5 · lost 1

Phi 3 Medium 128k Instructwon 5 · lost 1

Apertus 70B Instructwon 5 · lost 1

Granite 4.0 H Microwon 5 · lost 1

Phi 3.5 Mini Instructwon 5 · lost 1

Aya Expanse 8Bwon 7 · lost 2

Amazon Nova Litewon 7 · lost 2

Aya Expanse 32Bwon 7 · lost 2

Gemma 3 4B ITwon 7 · lost 2

Command Awon 7 · lost 2

Grok 4.1 Fastwon 7 · lost 2

Llama 3.2 1B Instructwon 6 · lost 2

Phi-3 Mini 128K Instructwon 6 · lost 2

Llama 2 13B Chatwon 6 · lost 2

Phi-3 Mini 4K Instructwon 6 · lost 2

Phi-3 Small 8K Instructwon 6 · lost 2

Granite 3.1 2B Instructwon 6 · lost 2

Gemma 2 2B ITwon 6 · lost 2

Granite 3.1 8B Instructwon 6 · lost 2

Llama 3.1 8B Instructwon 6 · lost 2

Llama 3.1 Tulu 3 8Bwon 6 · lost 2

GPT-4won 6 · lost 2

Jamba 1.5 Largewon 6 · lost 2

Magistral Mediumwon 6 · lost 2

Qwen3 30B A3B Instructwon 6 · lost 2

DeepSeek V4 Flashwon 6 · lost 2

MiMo V2.6 Flashwon 6 · lost 2

Gemini 3.6 Flashwon 6 · lost 2

Mistral Instruct v0.3 (7B)won 4 · lost 2

Hunyuan A13B Instructwon 4 · lost 2

Fuguwon 4 · lost 2

Granite 3.2 2B Instructwon 4 · lost 2

Granite 3.0 3B A800M Instructwon 4 · lost 2

Reflection Llama 3.1 70Bwon 4 · lost 2

Qwen2 VL 72Bwon 4 · lost 2

Granite 3.1 3B A800M Instructwon 4 · lost 2

Phi 3 Small 128k Instructwon 4 · lost 2

GPT-5.6 Astrawon 4 · lost 2

GPT OSS Safeguard 20Bwon 4 · lost 2

Kimi K2 Thinkingwon 4 · lost 2

EAI Llama 3.1 8B Instruct SageAlignwon 4 · lost 2

SeaLLM 7B V2won 4 · lost 2

K2 Chatwon 4 · lost 2

Llama 3.1 Tulu 3 8B SFTwon 4 · lost 2

Llama 3.1 Tulu 3 8B DPOwon 4 · lost 2

Krutrim 2 Instructwon 4 · lost 2

Phi 3.5 MoE Instructwon 4 · lost 2

Llama 3.2 Vision (11B)won 4 · lost 2

Mistral Small 3 24B Instructwon 6 · lost 3

Llama 4 Scout Instructwon 6 · lost 3

Llama 4 Maverick Instructwon 6 · lost 3

Gemma 3 27B ITwon 6 · lost 3

DeepSeek V3won 6 · lost 3

Grok 3won 6 · lost 3

DeepSeek V3.1won 6 · lost 3

DeepSeek R1won 6 · lost 3

GLM-4.6won 6 · lost 3

Gemini 2.5 Prowon 6 · lost 3

Kimi K2.5won 6 · lost 3

Gemma 4 31Bwon 6 · lost 3

DeepSeek V4 Prowon 6 · lost 3

Claude 3 Haikuwon 5 · lost 3

Llama 3 70B Instructwon 5 · lost 3

QwQ 32Bwon 5 · lost 3

Gemini 2.0 Flash-Litewon 5 · lost 3

NVIDIA Nemotron 3 Super 120B A12Bwon 5 · lost 3

GLM-4.5won 5 · lost 3

Grok 4won 5 · lost 3

NVIDIA Nemotron 3 Ultra 550B A55Bwon 5 · lost 3

Gemma 4 26B A4Bwon 5 · lost 3

Grok 4.3won 5 · lost 3

GLM-5.3 Flashwon 5 · lost 3

GLM-5.2won 5 · lost 3

MiMo V2.6 Prowon 5 · lost 3

Llama 2 70B Chatwon 4 · lost 3

Llama 3.3 70B Instructwon 5 · lost 4

Gemma 3 12B ITwon 5 · lost 4

Mercury 2won 5 · lost 4

Qwen3.5 35B A3Bwon 5 · lost 4

Qwen3.5 27Bwon 5 · lost 4

Gemini 2.5 Flashwon 5 · lost 4

Qwen3.5 122B A10Bwon 5 · lost 4

Qwen3 235B A22B Instructwon 5 · lost 4

DeepSeek V3.2won 5 · lost 4

GPT-6 Solwon 5 · lost 4

Kimi K2.6won 5 · lost 4

Dolphin 2.5 Mixtral 8x7bwon 3 · lost 3

Qwen2 57B A14B Instructwon 3 · lost 3

Smaug Llama 3 70B Instructwon 3 · lost 3

EAI SageAlign 8B LoRAwon 3 · lost 3

Titan Text Express V1won 3 · lost 3

Internlm2 Chat 20Bwon 3 · lost 3

Nova Premierwon 3 · lost 3

Fugu Ultra V2won 3 · lost 3

Llama 3.2 Vision (90B)won 3 · lost 3

Llama 2 7B Chatwon 3 · lost 3

GLM-4.5 Airwon 3 · lost 3

Gemini 3 Prowon 3 · lost 3

Qwen2 72B Instructwon 4 · lost 4

Llama 3.1 70B Instructwon 4 · lost 4

Llama 3.1 Nemotron 70B Instructwon 4 · lost 4

Gemini 1.5 Flashwon 4 · lost 4

GPT-4o miniwon 4 · lost 4

Qwen Maxwon 4 · lost 4

GPT-4.1 nanowon 4 · lost 4

Llama 3.1 405B Instructwon 4 · lost 4

Gemini 1.5 Prowon 4 · lost 4

Gemini 2.0 Flashwon 4 · lost 4

GPT-4.1 miniwon 4 · lost 4

Qwen3 VL 235B A22B Instructwon 4 · lost 4

Mistral Large 4won 4 · lost 4

MiniMax M3won 4 · lost 4

GPT-6 Lunawon 4 · lost 4

GLM-5.1won 4 · lost 4

MiMo V2.5 Prowon 4 · lost 4

Qwen3.7 Maxwon 4 · lost 4

Gemini 3.5 Flashwon 4 · lost 4

Gemini 3.8 Flashwon 4 · lost 4

Phi 4won 4 · lost 5

Amazon Nova Prowon 4 · lost 5

GPT OSS 120Bwon 4 · lost 5

Kimi K2won 4 · lost 5

GPT-5.6 Solwon 4 · lost 5

Claude Sonnet 4.6won 3 · lost 4

Qwen3.8 Maxwon 3 · lost 4

Claude Opus 4.6won 3 · lost 4

Qwen2.5 72B Instructwon 3 · lost 5

GPT OSS 20Bwon 3 · lost 5

Qwen3.5 397B A17Bwon 3 · lost 5

GPT-5.6 Lunawon 3 · lost 5

Grok 4.5won 3 · lost 5

Claude Opus 5won 3 · lost 5

Sarvam 105Bwon 2 · lost 4

Llama 3 8B Instruct MopeyMulewon 2 · lost 4

Meta SecAlign 8Bwon 2 · lost 4

Qwen3 Next 80B A3B Thinkingwon 2 · lost 4

Gemini 2.5 Flash-Litewon 2 · lost 4

GPT-4owon 3 · lost 6

O4 Miniwon 3 · lost 6

Claude Haiku 4.5won 3 · lost 6

Claude Opus 4won 3 · lost 6

Claude Sonnet 4.5won 3 · lost 6

GPT-5.4won 3 · lost 6

GPT-5.5won 3 · lost 6

Claude 3 Sonnetwon 2 · lost 5

Claude 3.5 Haikuwon 2 · lost 6

MiniMax M2won 2 · lost 6

Claude 3.7 Sonnetwon 2 · lost 6

Grok 4.6won 2 · lost 6

GPT-5.6 Terrawon 2 · lost 6

Claude Opus 4.8won 2 · lost 6

GPT-5 nanowon 2 · lost 7

GPT-5 miniwon 2 · lost 7

Claude Sonnet 4won 2 · lost 7

GPT-4.1won 2 · lost 7

MiniMax M2.7won 2 · lost 7

GPT-5won 2 · lost 7

GPT-5.2won 2 · lost 7

GPT-5.1won 2 · lost 7

Claude Opus 4.7won 2 · lost 7

Claude Opus 5.5won 2 · lost 7

Cogito 671B V2 P1won 1 · lost 5

Foundation Sec 8B Instructwon 1 · lost 5

Mistral NeMo Minitron 8B Instructwon 1 · lost 5

Gemma 2 27B ITwon 1 · lost 7

GPT-4 Turbowon 1 · lost 7

O1 Miniwon 1 · lost 7

O3 Miniwon 1 · lost 7

Claude 3.5 Sonnetwon 1 · lost 7

O1won 1 · lost 7

O3won 1 · lost 7

Grok 4.7won 1 · lost 7

Inklingwon 1 · lost 7

Hy3won 1 · lost 7

Muse Spark 1.1won 1 · lost 7

Apriel 1.5 15B Thinkerwon 0 · lost 6

Claude 3 Opuswon 0 · lost 8

Claude Sonnet 5won 0 · lost 8

§ 3 · Sources

Where the numbers come from

3 publications, 8 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-11

LMArena Text 1287

Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-11

Enkrypt · Jailbreak risk 10.1%Enkrypt · Harmful content risk 14.4%Enkrypt · CBRN risk 11.3%Enkrypt · Toxicity risk 0.4%Enkrypt · Bias risk 81.4%Enkrypt · Insecure code risk 24%

Vectara Hallucination Leaderboard ↗1 measureread 2026-11-11

Vectara · Factual consistency 94.8%

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