The LLM benchmark aggregator.

Nova Pro

Amazon

Strongest in Factual grounding (#10 of 101), weakest in Human preference (#227 of 342). Above par in 5 of 11 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Inkling 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.

Safety53−8.5#104/3372/3

Factual grounding62.3−8.3#10/1011/1

Harm refusal56.7−4.9#39/3001/2

Jailbreak resistance55.8−9.1#105/2721/1

Toxicity avoidance53−6#153/2721/1

Fairness45.5−24.5#183/3001/2

Secure code40.9−25.6#213/2741/1

Agents44.8−23.3#186/2681/5

Tool use40.7−33.3#64/811/1

Human preference46.4−21.1#227/3421/1

§ 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 Nova Pro, left for the other.

Gemma 2B Itwon 8 · lost 0

Smollm2 1.7B Instructwon 8 · lost 0

Nous Hermes 2 Mixtral 8x7b Dpowon 8 · lost 0

Jamba 1.5 Largewon 8 · lost 0

Llama 3.2 3B Instructwon 10 · lost 0

Command R Pluswon 8 · lost 1

Gemma 7B Itwon 7 · lost 1

Mistral 7B Instruct V0.2won 7 · lost 1

DeepSeek LLM 67B Chatwon 7 · lost 1

DBRX Instructwon 7 · lost 1

GPT-3.5 Turbowon 7 · lost 1

Llama 3 8B Instructwon 7 · lost 1

Jamba 1.5 Miniwon 7 · lost 1

Jamba Mini 1.7won 6 · lost 1

Llama 3.2 1B Instructwon 8 · lost 2

Phi-4 Mini Instructwon 6 · lost 2

Gemma 4 E4Bwon 6 · lost 2

Zephyr 7B Betawon 6 · lost 2

Phi 3 Mini 4k Instructwon 6 · lost 2

Granite 3.0 2B Instructwon 6 · lost 2

Phi 3 Small 8k Instructwon 6 · lost 2

Granite 3.1 2B Instructwon 6 · lost 2

Qwen1.5 14B Chatwon 6 · lost 2

Gemma 2 2B Itwon 6 · lost 2

Gemma 2 9B Itwon 6 · lost 2

Mistral Small 24B Instructwon 6 · lost 2

Jamba Large 1.7won 5 · lost 2

Gemma 4 E2Bwon 5 · lost 2

Nemotron 3 Ultra 550B A55Bwon 5 · lost 2

Llama 3.1 8B Instructwon 7 · lost 3

Nova Litewon 6 · lost 3

GPT-4won 6 · lost 3

Nova Microwon 7 · lost 4

Gemma 3 4B Itwon 7 · lost 4

Mistral Smallwon 7 · lost 4

Gemma 4 31Bwon 7 · lost 4

Command R7Bwon 5 · 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

Phi 3 Medium 4k Instructwon 5 · lost 3

DeepSeek V3won 6 · lost 4

DeepSeek R1won 6 · lost 4

DeepSeek V4 Prowon 6 · lost 4

Llama 3.3 Instruct Turbo (70B)won 4 · lost 3

Gemma 4 12Bwon 4 · lost 3

Ling 3.0 Flashwon 4 · lost 3

Grok Build 0.1won 4 · lost 3

Ling 3.0 Flash VLwon 4 · lost 3

C4ai Aya Expanse 8Bwon 5 · lost 4

C4ai Aya Expanse 32Bwon 5 · lost 4

Grok 3won 5 · lost 4

DeepSeek V4 Flashwon 5 · lost 4

Grok 4.3won 5 · lost 4

GLM-4.6won 6 · lost 5

Grok 4.1 Fastwon 6 · lost 5

Granite 3.2 8B Instructwon 4 · lost 4

Llama 3.1 Tulu 3 8Bwon 4 · lost 4

Claude 3 Haikuwon 4 · lost 4

Llama 3 70B Instructwon 4 · lost 4

Magistral Mediumwon 4 · lost 4

Gemini 1.5 Flashwon 4 · lost 4

QwQ 32Bwon 4 · lost 4

Gemini 1.5 Prowon 4 · lost 4

Gemini 2.0 Flash Litewon 4 · lost 4

Qwen3 Vl 235B A22B Instructwon 4 · lost 4

Mimo V2.6 Flashwon 4 · lost 4

Granite 3.1 8B Instructwon 5 · lost 5

Gemma 4 26B A4Bwon 5 · lost 5

Gemini 2.5 Prowon 5 · lost 5

GPT-6 Solwon 5 · lost 5

Kimi K2.6won 5 · lost 5

Llama 4 Scout Instructwon 5 · lost 6

Gemma 3 12B Itwon 5 · lost 6

Command Awon 5 · lost 6

Gemini 2.5 Flashwon 5 · lost 6

DeepSeek V3.2won 5 · lost 6

Qwen3 8Bwon 4 · lost 5

GPT OSS 20Bwon 4 · lost 5

NVIDIA Nemotron 3 Super 120B A12Bwon 4 · lost 5

Qwen3.7 Maxwon 4 · lost 5

Gemini 3.6 Flashwon 4 · lost 5

Granite 4.0 H Smallwon 3 · lost 4

Kimi K2.7 Codewon 3 · lost 4

Qwen3 Next 80B A3B Thinkingwon 3 · lost 4

GPT-4.1 Nanowon 4 · lost 6

Qwen3 30B A3B Instructwon 4 · lost 6

Grok 4won 4 · lost 6

Kimi K2.5won 4 · lost 6

GLM-5.2won 4 · lost 6

GPT-5.5won 4 · lost 6

GPT-5.6 Solwon 4 · lost 6

Qwen2 72B Instructwon 3 · lost 5

Gemma 2 27B Itwon 3 · lost 5

Gemini 2.0 Flashwon 3 · lost 5

GLM-4.5won 3 · lost 5

Claude Sonnet 4.6won 3 · lost 5

Gemini 3 Prowon 3 · lost 5

Mistral Largewon 4 · lost 7

Llama 4 Maverick Instructwon 4 · lost 7

Gemma 3 27B Itwon 4 · lost 7

Kimi K2won 4 · lost 7

Qwen3.5 27Bwon 3 · lost 6

GPT-6 Lunawon 3 · lost 6

GLM-5.1won 3 · lost 6

Grok 4.5won 3 · lost 6

Mimo V2.5 Prowon 3 · lost 6

GLM-5.3 Flashwon 3 · lost 6

Gemini 3.5 Flashwon 3 · lost 6

Qwen3.8 Maxwon 3 · lost 6

Gemini 3.8 Flashwon 3 · lost 6

GPT OSS 120Bwon 3 · lost 7

GPT-4.1 Miniwon 3 · lost 7

Qwen3.5 35B A3Bwon 3 · lost 7

Qwen3.5 122B A10Bwon 3 · lost 7

MiniMax M3won 3 · lost 7

GPT-5.6 Lunawon 3 · lost 7

GPT-5.6 Terrawon 3 · lost 7

GPT-5.4won 3 · lost 7

Claude Opus 4.6won 2 · lost 5

GPT-4.1won 3 · lost 8

Qwen3 235B A22B Instructwon 3 · lost 8

Claude 3 Sonnetwon 2 · lost 6

GPT-4o Miniwon 2 · lost 7

Claude 3.5 Haikuwon 2 · lost 7

GPT-4owon 2 · lost 7

O3 Miniwon 2 · lost 7

Claude Opus 4won 2 · lost 7

Qwen3.5 397B A17Bwon 2 · lost 7

Mimo V2.6 Prowon 2 · lost 7

Claude Opus 5won 2 · lost 7

Claude Sonnet 4won 2 · lost 8

GPT-5.1won 2 · lost 8

Phi 4won 2 · lost 9

GPT-5 Miniwon 2 · lost 9

O4 Miniwon 2 · lost 9

Qwen2.5 72B Instructwon 1 · lost 7

Qwen Maxwon 1 · lost 7

MiniMax M2won 1 · lost 7

Gemini 2.5 Flash Litewon 1 · lost 7

Claude 3.7 Sonnetwon 1 · lost 8

MiniMax M2.7won 1 · lost 8

Grok 4.7won 1 · lost 8

Grok 4.6won 1 · lost 8

Muse Spark 1.1won 1 · lost 8

O3won 1 · lost 9

GPT-5won 1 · lost 9

Claude Opus 4.7won 1 · lost 9

GPT-5 Nanowon 1 · lost 10

Claude Haiku 4.5won 1 · lost 10

GPT-5.2won 1 · lost 10

Claude Sonnet 4.5won 1 · lost 10

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

Hy3won 0 · lost 9

Claude Opus 4.8won 0 · lost 9

Claude Opus 5.5won 0 · lost 9

Inklingwon 0 · lost 10

Claude Sonnet 5won 0 · lost 10

§ 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 2026-09-26

LMArena Text 1290

BFCL ↗1 measureread 2026-09-26

BFCL v4 24.97%

Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-09-26

Enkrypt · Jailbreak risk 7.9%Enkrypt · Harmful content risk 17.8%Enkrypt · CBRN risk 5.5%Enkrypt · Toxicity risk 4.2%Enkrypt · Bias risk 84.8%Enkrypt · Insecure code risk 52%

Vectara Hallucination Leaderboard ↗1 measureread 2026-09-26

Vectara · Factual consistency 94.9%

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