The LLM benchmark aggregator.

Amazon Nova Lite

Amazon

Strongest in Factual grounding (#25 of 104), weakest in Human preference (#261 of 354). Above par in 5 of 9 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 4.8 and Claude Sonnet 5 and ahead of GPT-5.6 Sol and Kimi K2.6.

§ 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.

Safety53.7−7.7#77/3292/3

Factual grounding59.8−10.9#25/1041/1

Harm refusal56.4−5.1#42/2921/2

Jailbreak resistance56.9−8.1#82/2681/1

Toxicity avoidance52.9−6.1#152/2681/1

Secure code49−17.2#163/2701/1

Fairness45.4−24.6#182/2921/2

Human preference43.2−25.6#261/3541/1

§ 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 Amazon Nova Lite, 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

RakutenAI 7B Instructwon 6 · lost 0

Falcon Mamba 7B Instructwon 6 · lost 0

Qwen2.5 0.5B Instructwon 6 · lost 0

Jamba 1.6 Miniwon 6 · lost 0

Granite 3.0 1B A400M Instructwon 6 · lost 0

SeaLLMs V3 7B Chatwon 6 · lost 0

Gemma 2B ITwon 8 · lost 0

SmolLM2 1.7B Instructwon 8 · lost 0

Nous Hermes 2 Mixtral 8x7B DPOwon 8 · lost 0

Llama 3.2 3B Instructwon 8 · lost 0

DBRX Instructwon 8 · lost 0

Mixtral 8x7B Instructwon 8 · lost 0

GPT-3.5 Turbowon 8 · lost 0

OLMo 7B Instructwon 7 · lost 1

Zephyr 7B Betawon 7 · lost 1

Gemma 7B ITwon 7 · lost 1

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

Granite 3.1 2B Instructwon 7 · lost 1

DeepSeek LLM 67B Chatwon 7 · lost 1

Llama 3.1 8B Instructwon 7 · lost 1

Jamba 1.5 Miniwon 7 · lost 1

Jamba Mini 1.7won 6 · lost 1

Jamba Large 1.7won 6 · lost 1

Qwen1.5 14B Chatwon 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

Laguna Xs 2.1won 5 · lost 1

SmolLM2 360M Instructwon 5 · lost 1

CodeLlama 7B Instructwon 5 · lost 1

Magistral Small 1.2won 5 · lost 1

Aya 23 8Bwon 5 · lost 1

Falcon H1 0.5B Instructwon 5 · lost 1

SEA LION V1 7B ITwon 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

NexusRaven V2 13Bwon 5 · lost 1

SmolLM 360M Instructwon 5 · lost 1

Granite 3.2 8B Instructwon 5 · lost 1

Open Codestral Mambawon 5 · lost 1

Qwen2.5 3B Instructwon 5 · lost 1

Aya 23 35Bwon 5 · lost 1

Jamba 1.6 Largewon 5 · lost 1

Jamba Instructwon 5 · lost 1

Yi 1.5 9B Chatwon 5 · lost 1

Sarvam 1won 5 · lost 1

Qwen2.5 7B Instruct 1Mwon 5 · lost 1

DeepSeek Reasonerwon 5 · lost 1

Komodo 7B Basewon 5 · lost 1

Granite 3.2 2B Instructwon 5 · lost 1

DeepSeek Chatwon 5 · lost 1

Qwen2.5 32B Instructwon 5 · lost 1

GLM-5 Turbowon 5 · lost 1

Qwen 2.5 Instruct (7B)won 5 · lost 1

EAI Llama 3.1 8B Instruct SageAlignwon 5 · lost 1

Llama 3.2 1B Instructwon 6 · lost 2

Granite 3.0 2B Instructwon 6 · lost 2

Phi-3 Small 8K Instructwon 6 · lost 2

Phi-3 Medium 4K Instructwon 6 · lost 2

Gemma 2 2B ITwon 6 · lost 2

Granite 3.1 8B Instructwon 6 · lost 2

Mixtral 8x22B Instructwon 6 · lost 2

Jamba 1.5 Largewon 6 · lost 2

Phi-4 Mini Instructwon 5 · lost 2

Phi-3 Mini 4K Instructwon 5 · lost 2

LFM2 350Mwon 4 · lost 2

GLM-4 9B Chatwon 4 · lost 2

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

Qwen2 7B Instructwon 4 · lost 2

OLMo 2 7B Instructwon 4 · lost 2

Laguna S 2.1won 4 · lost 2

Grok Build 0.1won 4 · lost 2

Ling 3.0 Flash VLwon 4 · lost 2

LFM2 700Mwon 4 · lost 2

Ling 3.0 Flashwon 4 · lost 2

LFM2 1.2Bwon 4 · lost 2

Gemma 4 E2Bwon 4 · lost 2

Gemma 4 E4Bwon 4 · lost 2

Qwen2.5 1.5B Instructwon 4 · lost 2

WizardLM 2.8x22Bwon 4 · lost 2

IBM Granite 4.0 Microwon 4 · lost 2

Gemma 4 12Bwon 4 · lost 2

Hunyuan A13B Instructwon 4 · lost 2

Granite 3.0 3B A800M Instructwon 4 · lost 2

Gemma2 9B Cpt Sea Lionv3 Instructwon 4 · lost 2

Reflection Llama 3.1 70Bwon 4 · lost 2

LongWriter Glm4 9Bwon 4 · lost 2

Qwen2 VL 72Bwon 4 · lost 2

Granite 3.1 3B A800M Instructwon 4 · lost 2

Sarvam 30Bwon 4 · lost 2

Qwen2.5 14B Instructwon 4 · lost 2

Phi 3 Small 128k Instructwon 4 · lost 2

GPT-5.6 Astrawon 4 · lost 2

Apertus 70B Instructwon 4 · lost 2

Granite 4.0 H Microwon 4 · lost 2

Phi 3.5 Mini Instructwon 4 · lost 2

Krutrim 2 Instructwon 4 · lost 2

Amazon Nova Microwon 6 · lost 3

Command R+won 6 · lost 3

Gemma 3 4B ITwon 6 · lost 3

GLM-4.6won 6 · lost 3

Grok 4.1 Fastwon 6 · lost 3

Gemma 4 31Bwon 6 · lost 3

DeepSeek V4 Prowon 6 · lost 3

Phi-3 Mini 128K Instructwon 5 · lost 3

Starling LM 7B Betawon 5 · lost 3

Granite 3.0 8B Instructwon 5 · lost 3

Llama 3.1 Tulu 3 8Bwon 5 · lost 3

Llama 3 8B Instructwon 5 · lost 3

Llama 3.1 70B Instructwon 5 · lost 3

Magistral Mediumwon 5 · lost 3

QwQ 32Bwon 5 · lost 3

Gemini 1.5 Prowon 5 · lost 3

Gemini 2.0 Flash-Litewon 5 · lost 3

Qwen3 30B A3B Instructwon 5 · lost 3

DeepSeek V3won 5 · lost 3

NVIDIA Nemotron 3 Ultra 550B A55Bwon 5 · lost 3

DeepSeek V4 Flashwon 5 · lost 3

Grok 4.3won 5 · lost 3

MiMo V2.6 Flashwon 5 · lost 3

Qwen3 8Bwon 4 · lost 3

GLM-4.5won 4 · lost 3

Llama 3.3 70B Instructwon 5 · lost 4

Command Awon 5 · lost 4

Gemini 2.5 Flashwon 5 · lost 4

Grok 3won 5 · lost 4

DeepSeek R1won 5 · lost 4

DeepSeek V3.2won 5 · lost 4

Gemini 2.5 Prowon 5 · lost 4

GPT-6 Solwon 5 · lost 4

Kimi K2.6won 5 · lost 4

GPT-5.6 Solwon 5 · lost 4

Mimo V2.6 Pro Ultraspeedwon 3 · lost 3

Kimi K2.7 Codewon 3 · lost 3

Fuguwon 3 · lost 3

Dolphin 2.5 Mixtral 8x7bwon 3 · lost 3

Apertus 8B Instructwon 3 · lost 3

Qwen2.5 14B Instruct 1Mwon 3 · lost 3

Qwen2 57B A14B Instructwon 3 · lost 3

Smaug Llama 3 70B Instructwon 3 · lost 3

GPT OSS Safeguard 20Bwon 3 · lost 3

Kimi K2 Thinkingwon 3 · lost 3

Llama 3.1 Tulu 3 8B SFTwon 3 · lost 3

EAI SageAlign 8B LoRAwon 3 · lost 3

Fugu Ultra V2won 3 · lost 3

GLM-4.5 Airwon 3 · lost 3

Gemini 3 Prowon 3 · lost 3

Llama 2 70B Chatwon 4 · lost 4

Aya Expanse 8Bwon 4 · lost 4

Gemma 2 9B ITwon 4 · lost 4

Gemini 1.5 Flashwon 4 · lost 4

GPT OSS 20Bwon 4 · lost 4

Llama 4 Scout Instructwon 4 · lost 4

NVIDIA Nemotron 3 Super 120B A12Bwon 4 · lost 4

Gemini 2.0 Flashwon 4 · lost 4

Gemma 3 27B ITwon 4 · lost 4

GPT-4.1 miniwon 4 · lost 4

Grok 4won 4 · lost 4

Qwen3 VL 235B A22B Instructwon 4 · lost 4

GPT-6 Lunawon 4 · lost 4

GPT-5.6 Lunawon 4 · lost 4

GLM-5.1won 4 · lost 4

Qwen3.7 Maxwon 4 · lost 4

GLM-5.2won 4 · lost 4

Gemini 3.6 Flashwon 4 · lost 4

Qwen3.8 Maxwon 4 · lost 4

Mistral Small 3 24B Instructwon 4 · lost 5

Llama 4 Maverick Instructwon 4 · lost 5

Gemma 3 12B ITwon 4 · lost 5

Mercury 2won 4 · lost 5

Qwen3.5 35B A3Bwon 4 · lost 5

Qwen3.5 27Bwon 4 · lost 5

DeepSeek V3.1won 4 · lost 5

Qwen3.5 122B A10Bwon 4 · lost 5

Kimi K2won 4 · lost 5

Gemma 4 26B A4Bwon 4 · lost 5

Kimi K2.5won 4 · lost 5

GPT-5.5won 4 · lost 5

Claude Opus 4.6won 3 · lost 4

Llama 2 7B Chatwon 3 · lost 5

Llama 2 13B Chatwon 3 · lost 5

GPT-4won 3 · lost 5

Llama 3 70B Instructwon 3 · lost 5

Amazon Nova Prowon 3 · lost 5

GPT-4.1 nanowon 3 · lost 5

Llama 3.1 405B Instructwon 3 · lost 5

Mistral Large 4won 3 · lost 5

MiniMax M3won 3 · lost 5

Grok 4.5won 3 · lost 5

MiMo V2.5 Prowon 3 · lost 5

GPT-5.6 Terrawon 3 · lost 5

GLM-5.3 Flashwon 3 · lost 5

Gemini 3.5 Flashwon 3 · lost 5

Gemini 3.8 Flashwon 3 · lost 5

Llama 3.2 Vision (11B)won 2 · lost 4

Titan Text Express V1won 2 · lost 4

Nova Premierwon 2 · lost 4

Llama 3.2 Vision (90B)won 2 · lost 4

Cogito 671B V2 P1won 2 · lost 4

Qwen3 Next 80B A3B Thinkingwon 2 · lost 4

GPT OSS 120Bwon 3 · lost 6

O4 Miniwon 3 · lost 6

GPT-4.1won 3 · lost 6

Qwen3 235B A22B Instructwon 3 · lost 6

GPT-5.1won 3 · lost 6

GPT-5.4won 3 · lost 6

Claude Sonnet 4.6won 2 · lost 5

Claude 3 Haikuwon 2 · lost 6

Llama 3.1 Nemotron 70B Instructwon 2 · lost 6

Qwen2.5 72B Instructwon 2 · lost 6

GPT-4o miniwon 2 · lost 6

Qwen Maxwon 2 · lost 6

Qwen3.5 397B A17Bwon 2 · lost 6

Grok 4.6won 2 · lost 6

MiMo V2.6 Prowon 2 · lost 6

Claude Opus 5won 2 · lost 6

Phi 4won 2 · lost 7

Aya Expanse 32Bwon 2 · lost 7

Granite 4.0 H Smallwon 2 · lost 7

GPT-4owon 2 · lost 7

GPT-5 miniwon 2 · lost 7

Claude Sonnet 4won 2 · lost 7

Claude Haiku 4.5won 2 · lost 7

MiniMax M2.7won 2 · lost 7

Claude Opus 4won 2 · lost 7

Claude Sonnet 4.5won 2 · lost 7

Internlm2 Chat 20Bwon 1 · lost 5

Sarvam 105Bwon 1 · lost 5

Llama 3 8B Instruct MopeyMulewon 1 · lost 5

Foundation Sec 8B Instructwon 1 · lost 5

Apriel 1.5 15B Thinkerwon 1 · lost 5

Mistral NeMo Minitron 8B Instructwon 1 · lost 5

Gemini 2.5 Flash-Litewon 1 · lost 5

Qwen2 72B Instructwon 1 · lost 7

Gemma 2 27B ITwon 1 · lost 7

Claude 3.5 Haikuwon 1 · lost 7

MiniMax M2won 1 · lost 7

O3 Miniwon 1 · lost 7

Claude 3.7 Sonnetwon 1 · lost 7

O3won 1 · lost 7

Grok 4.7won 1 · lost 7

Muse Spark 1.1won 1 · lost 7

GPT-5 nanowon 1 · lost 8

GPT-5won 1 · lost 8

GPT-5.2won 1 · lost 8

Claude Opus 4.7won 1 · lost 8

Claude Opus 5.5won 1 · lost 8

Meta SecAlign 8Bwon 0 · lost 6

Claude 3 Sonnetwon 0 · lost 8

Claude 3 Opuswon 0 · lost 8

GPT-4 Turbowon 0 · lost 8

O1 Miniwon 0 · lost 8

Claude 3.5 Sonnetwon 0 · lost 8

O1won 0 · lost 8

Inklingwon 0 · lost 8

Hy3won 0 · lost 8

Claude Sonnet 5won 0 · lost 8

Claude Opus 4.8won 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 2026-11-10

LMArena Text 1260

Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10

Enkrypt · Jailbreak risk 7%Enkrypt · Harmful content risk 15.6%Enkrypt · CBRN risk 7.3%Enkrypt · Toxicity risk 4.2%Enkrypt · Bias risk 85%Enkrypt · Insecure code risk 35.1%

Vectara Hallucination Leaderboard ↗1 measureread 2026-11-10

Vectara · Factual consistency 93.9%

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