Request a Pilot
‹ PublicAI Index

The LLM benchmark aggregator.

Amazon Nova Micro

Amazon

Strongest in Factual grounding (#18 of 104), weakest in Human preference (#267 of 354). Above par in 6 of 11 scopes. Among the models it meets almost everywhere, it finishes behind Phi 4 and Claude Opus 4.8 and ahead of Grok 4.1 Fast and GLM-4.6.

§ 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.

Safety53.6#80/329
Factual grounding61.3#18/104
Harm refusal54.5#77/292
Jailbreak resistance56.7#88/268
Toxicity avoidance54.6#117/268
Secure code51.6#136/270
Fairness44#212/292
Agents45.3#214/298
Tool use38.7#68/81
Human preference41.4#267/354
Human preference41.4#267/354

§ 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 Micro, left for the other.

SmolLM2 1.7B Instructwon 8 · lost 0
Nous Hermes 2 Mixtral 8x7B DPOwon 8 · lost 0
DBRX Instructwon 8 · lost 0
GPT-3.5 Turbowon 8 · lost 0
Llama 3.2 3B Instructwon 10 · lost 0
OLMo 7B Instructwon 7 · lost 1
Gemma 2B ITwon 7 · lost 1
Zephyr 7B Betawon 7 · lost 1
Gemma 7B ITwon 7 · lost 1
Granite 3.0 2B Instructwon 7 · lost 1
Granite 3.1 2B Instructwon 7 · lost 1
DeepSeek LLM 67B Chatwon 7 · lost 1
Qwen1.5 14B Chatwon 7 · lost 1
Mixtral 8x7B 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
Gemma 4 E2Bwon 6 · lost 1
Magistral Small 1.2won 6 · lost 1
Llama 3.1 8B Instructwon 8 · lost 2
Phi-4 Mini Instructwon 6 · lost 2
Mistral 7B Instruct v0.2won 6 · lost 2
Phi-3 Small 8K Instructwon 6 · lost 2
Starling LM 7B Betawon 6 · lost 2
Phi-3 Medium 4K Instructwon 6 · lost 2
Gemma 2 2B ITwon 6 · lost 2
Llama 3 8B Instructwon 6 · lost 2
Mixtral 8x22B Instructwon 6 · lost 2
QwQ 32Bwon 6 · lost 2
Gemma 3 4B ITwon 8 · lost 3
Gemma 4 E4Bwon 5 · lost 2
Gemma 4 12Bwon 5 · lost 2
Ling 3.0 Flash VLwon 5 · lost 2
Llama 3.2 1B Instructwon 7 · lost 3
DeepSeek V3won 7 · lost 3
Gemini 2.5 Prowon 7 · lost 3
Gemma 4 31Bwon 7 · lost 3
Command R+won 6 · lost 3
Grok 3won 6 · lost 3
MiMo V2.6 Flashwon 6 · lost 3
Command Awon 7 · lost 4
Granite 3.2 8B Instructwon 5 · lost 3
Command R7Bwon 5 · lost 3
Phi-3 Mini 128K Instructwon 5 · lost 3
Phi-3 Mini 4K Instructwon 5 · lost 3
Granite 3.0 8B Instructwon 5 · lost 3
Llama 3.1 Tulu 3 8Bwon 5 · lost 3
Jamba 1.5 Largewon 5 · lost 3
Llama 3.1 70B Instructwon 5 · lost 3
Magistral Mediumwon 5 · lost 3
Gemini 1.5 Prowon 5 · lost 3
Gemini 2.0 Flash-Litewon 5 · lost 3
GLM-4.5won 5 · lost 3
Granite 3.1 8B Instructwon 6 · lost 4
DeepSeek R1won 6 · lost 4
DeepSeek V4 Prowon 6 · lost 4
Ling 3.0 Flashwon 4 · lost 3
Grok Build 0.1won 4 · lost 3
Mistral Small 3 24B Instructwon 5 · lost 4
Qwen3.5 27Bwon 5 · lost 4
NVIDIA Nemotron 3 Ultra 550B A55Bwon 5 · lost 4
DeepSeek V4 Flashwon 5 · lost 4
Llama 3.3 70B Instructwon 6 · lost 5
GLM-4.6won 6 · lost 5
Grok 4.1 Fastwon 6 · lost 5
Gemma 2 9B ITwon 4 · lost 4
Gemini 1.5 Flashwon 4 · lost 4
Llama 3.1 405B Instructwon 4 · lost 4
Gemini 2.0 Flashwon 4 · lost 4
Qwen3 VL 235B A22B Instructwon 4 · lost 4
DeepSeek V3.1won 4 · lost 4
Grok 4.3won 4 · lost 4
GPT-4.1 nanowon 5 · lost 5
Mercury 2won 5 · lost 5
Qwen3 30B A3B Instructwon 5 · lost 5
Grok 4won 5 · lost 5
Qwen3.5 122B A10Bwon 5 · lost 5
Kimi K2.5won 5 · lost 5
GPT-6 Solwon 5 · lost 5
Kimi K2.6won 5 · lost 5
Llama 4 Scout Instructwon 5 · lost 6
Llama 4 Maverick Instructwon 5 · lost 6
Gemma 3 12B ITwon 5 · lost 6
Gemma 3 27B ITwon 5 · lost 6
Gemini 2.5 Flashwon 5 · lost 6
DeepSeek V3.2won 5 · lost 6
Qwen3 8Bwon 4 · lost 5
Aya Expanse 8Bwon 4 · lost 5
Gemma 4 26B A4Bwon 4 · lost 5
GPT-6 Lunawon 4 · lost 5
GLM-5.1won 4 · lost 5
Qwen3.7 Maxwon 4 · lost 5
GLM-5.3 Flashwon 4 · lost 5
Gemini 3.6 Flashwon 4 · lost 5
Qwen3.8 Maxwon 4 · lost 5
Gemini 3.8 Flashwon 4 · lost 5
Kimi K2.7 Codewon 3 · lost 4
Claude Opus 4.6won 3 · lost 4
GPT-4.1 miniwon 4 · lost 6
Qwen3.5 35B A3Bwon 4 · lost 6
GPT-5.5won 4 · lost 6
GPT-5.6 Solwon 4 · lost 6
Llama 2 13B Chatwon 3 · lost 5
Llama 2 70B Chatwon 3 · lost 5
Llama 3 70B Instructwon 3 · lost 5
Qwen2.5 72B Instructwon 3 · lost 5
Claude Sonnet 4.6won 3 · lost 5
Gemini 3 Prowon 3 · lost 5
Amazon Nova Prowon 4 · lost 7
Kimi K2won 4 · lost 7
Qwen3 235B A22B Instructwon 4 · lost 7
Amazon Nova Litewon 3 · lost 6
GPT-4won 3 · lost 6
GPT-4o miniwon 3 · lost 6
GPT OSS 20Bwon 3 · lost 6
NVIDIA Nemotron 3 Super 120B A12Bwon 3 · lost 6
Mistral Large 4won 3 · lost 6
MiniMax M3won 3 · lost 6
GPT-5.6 Lunawon 3 · lost 6
Grok 4.6won 3 · lost 6
Grok 4.5won 3 · lost 6
MiMo V2.5 Prowon 3 · lost 6
GPT-5.6 Terrawon 3 · lost 6
GLM-5.2won 3 · lost 6
Gemini 3.5 Flashwon 3 · lost 6
GPT OSS 120Bwon 3 · lost 7
Qwen3 Next 80B A3B Thinkingwon 2 · lost 5
O4 Miniwon 3 · lost 8
Llama 2 7B Chatwon 2 · lost 6
Claude 3 Haikuwon 2 · lost 6
Llama 3.1 Nemotron 70B Instructwon 2 · lost 6
Qwen Maxwon 2 · lost 6
Aya Expanse 32Bwon 2 · lost 7
Claude 3.5 Haikuwon 2 · lost 7
O3 Miniwon 2 · lost 7
Qwen3.5 397B A17Bwon 2 · lost 7
GPT-5.1won 2 · lost 7
MiMo V2.6 Prowon 2 · lost 7
Claude Opus 5won 2 · lost 7
GPT-4owon 2 · lost 8
Claude Sonnet 4won 2 · lost 8
GPT-4.1won 2 · lost 8
Claude Opus 5.5won 2 · lost 8
GPT-5 nanowon 2 · lost 9
GPT-5 miniwon 2 · lost 9
Claude Haiku 4.5won 2 · lost 9
GPT-5.2won 2 · lost 9
Claude Sonnet 4.5won 2 · lost 9
Gemma 2 27B ITwon 1 · lost 7
Claude 3.5 Sonnetwon 1 · lost 7
Gemini 2.5 Flash-Litewon 1 · lost 7
Claude Opus 4won 1 · lost 7
Granite 4.0 H Smallwon 1 · lost 8
Claude 3.7 Sonnetwon 1 · lost 8
Inklingwon 1 · lost 8
Hy3won 1 · lost 8
GPT-5.4won 1 · lost 8
Muse Spark 1.1won 1 · lost 8
MiniMax M2.7won 1 · lost 9
O3won 1 · lost 9
GPT-5won 1 · lost 9
Claude Opus 4.7won 1 · lost 9
Qwen2 72B Instructwon 0 · lost 8
Claude 3 Sonnetwon 0 · lost 8
Claude 3 Opuswon 0 · lost 8
GPT-4 Turbowon 0 · lost 8
O1 Miniwon 0 · lost 8
MiniMax M2won 0 · lost 8
O1won 0 · lost 8
Grok 4.7won 0 · lost 9
Claude Sonnet 5won 0 · lost 9
Claude Opus 4.8won 0 · lost 9
Phi 4won 0 · lost 11

§ 3 · Sources

Where the numbers come from

4 publications, 9 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1241
BFCL ↗1 measureread 2026-11-10
BFCL v4 22.29%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 7.2%Enkrypt · Harmful content risk 20.6%Enkrypt · CBRN risk 9.7%Enkrypt · Toxicity risk 3%Enkrypt · Bias risk 87.1%Enkrypt · Insecure code risk 29.8%
Vectara Hallucination Leaderboard ↗1 measureread 2026-11-10
Vectara · Factual consistency 94.5%

Badge

PublicAI Index badge for Amazon Nova Micro[![PublicAI Index](https://publicai.io/model-index/badge?model=amazon-nova-micro)](https://publicai.io/model-index/m/amazon-nova-micro)