The LLM benchmark aggregator.

Sarvam 1

Sarvam AI

Strongest in Fairness (#17 of 290, on 1 of its 2 boards), weakest in Secure code (#239 of 268). Above par in 1 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Grok 4.7 and ahead of Open Codestral Mamba and GLM-4.5.

§ 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.

Safety48.3−13.1#223/3271/3

Fairness66.3−3.7#17/2901/2

Jailbreak resistance48.6−16.4#180/2661/1

Toxicity avoidance48.6−10.4#206/2661/1

Harm refusal45.8−15.7#224/2901/2

Secure code31.7−34.5#239/2681/1

§ 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 Sarvam 1, left for the other.

Mistral Instruct v0.1 (7B)won 6 · lost 0

OLMo 7B Instructwon 6 · lost 0

SmolLM 1.7B Instructwon 6 · lost 0

RakutenAI 7B Chatwon 6 · lost 0

Phi 2won 6 · lost 0

SmolLM2 1.7B Instructwon 6 · lost 0

SmolLM2 360M Instructwon 6 · lost 0

OLMoE 1B-7B Instructwon 5 · lost 1

PowerMoE 3Bwon 5 · lost 1

Gemma 7B ITwon 5 · lost 1

H2o Danube3 500M Chatwon 5 · lost 1

PowerLM 3Bwon 5 · lost 1

Grok 4.1 Fastwon 5 · lost 1

LFM2 350Mwon 5 · lost 1

Falcon Mamba 7B Instructwon 5 · lost 1

GLM-4 9B Chatwon 5 · lost 1

Nous Hermes 2 Mixtral 8x7B DPOwon 5 · lost 1

Magistral Smallwon 5 · lost 1

Jamba Mini 1.7won 5 · lost 1

Grok 3won 5 · lost 1

Falcon H1 0.5B Instructwon 5 · lost 1

Grok Build 0.1won 5 · lost 1

DeepSeek R1won 5 · lost 1

Magistral Mediumwon 5 · lost 1

Jamba Large 1.7won 5 · lost 1

SmolLM 360M Instructwon 5 · lost 1

DeepSeek V3won 5 · lost 1

LFM2 700Mwon 4 · lost 1

DBRX Instructwon 4 · lost 2

Qwen3 30B A3B Instructwon 4 · lost 2

Laguna Xs 2.1won 4 · lost 2

RakutenAI 7B Instructwon 4 · lost 2

CodeLlama 7B Instructwon 4 · lost 2

Qwen2.5 0.5B Instructwon 4 · lost 2

Qwen2 7B Instructwon 4 · lost 2

Grok 4won 4 · lost 2

Gemma 2B ITwon 4 · lost 2

Magistral Small 1.2won 4 · lost 2

Aya 23 8Bwon 4 · lost 2

Laguna S 2.1won 4 · lost 2

SEA LION V1 7B ITwon 4 · lost 2

Qwen1.5 14B Chatwon 4 · lost 2

DeepSeek R1 Distill Qwen 7Bwon 4 · lost 2

DeepSeek R1 Distill Llama 8Bwon 4 · lost 2

Ling 3.0 Flash VLwon 4 · lost 2

Zephyr 7B Betawon 4 · lost 2

Gemini 3.6 Flashwon 4 · lost 2

Llama 3.1 70B Instructwon 4 · lost 2

Command R+won 4 · lost 2

DeepSeek V4 Flashwon 4 · lost 2

NexusRaven V2 13Bwon 4 · lost 2

Ling 3.0 Flashwon 4 · lost 2

Qwen3 8Bwon 4 · lost 2

GLM-5.2won 4 · lost 2

Gemini 3.5 Flashwon 4 · lost 2

NVIDIA Nemotron 3 Ultra 550B A55Bwon 4 · lost 2

GLM-4.6won 4 · lost 2

Grok 4.3won 4 · lost 2

Jamba 1.5 Miniwon 4 · lost 2

Qwen2.5 3B Instructwon 4 · lost 2

LFM2 1.2Bwon 4 · lost 2

NVIDIA Nemotron 3 Super 120B A12Bwon 4 · lost 2

MiniMax M3won 4 · lost 2

Kimi K2.6won 4 · lost 2

Qwen3.7 Maxwon 4 · lost 2

GLM-4.5won 4 · lost 2

Open Codestral Mambawon 3 · lost 2

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

OLMo 2 7B Instructwon 3 · lost 3

Mixtral 8x7B Instructwon 3 · lost 3

GPT-3.5 Turbowon 3 · lost 3

H2o Danube3 4B Chatwon 3 · lost 3

MiMo V2.6 Flashwon 3 · lost 3

Jamba 1.6 Miniwon 3 · lost 3

Command R7Bwon 3 · lost 3

Command Awon 3 · lost 3

Jamba 1.5 Largewon 3 · lost 3

Gemma 2 9B ITwon 3 · lost 3

DeepSeek LLM 67B Chatwon 3 · lost 3

Granite 3.2 8B Instructwon 3 · lost 3

Mimo V2.6 Pro Ultraspeedwon 3 · lost 3

Aya 23 35Bwon 3 · lost 3

Gemma 4 E2Bwon 3 · lost 3

Mixtral 8x22B Instructwon 3 · lost 3

DeepSeek V3.2won 3 · lost 3

Gemma 2 2B ITwon 3 · lost 3

GPT OSS 20Bwon 3 · lost 3

Gemini 2.5 Flashwon 3 · lost 3

Kimi K2won 3 · lost 3

GPT OSS 120Bwon 3 · lost 3

Mistral 7B Instruct v0.2won 2 · lost 4

Phi-4 Mini Instructwon 2 · lost 4

Granite 3.0 1B A400M Instructwon 2 · lost 4

QwQ 32Bwon 2 · lost 4

Jamba 1.6 Largewon 2 · lost 4

Jamba Instructwon 2 · lost 4

Yi 1.5 9B Chatwon 2 · lost 4

Gemma 4 E4Bwon 2 · lost 4

Qwen2.5 7B Instruct 1Mwon 2 · lost 4

Kimi K2.5won 2 · lost 4

Komodo 7B Basewon 2 · lost 4

Mistral Small 3 24B Instructwon 2 · lost 4

Llama 4 Scout Instructwon 2 · lost 4

Kimi K2.7 Codewon 2 · lost 4

Gemma 4 12Bwon 2 · lost 4

Fuguwon 2 · lost 4

MiMo V2.5 Prowon 2 · lost 4

Mistral Large 4won 2 · lost 4

DeepSeek V3.1won 2 · lost 4

Llama 3.3 70B Instructwon 2 · lost 4

Gemini 2.0 Flash-Litewon 2 · lost 4

Starling LM 7B Betawon 2 · lost 4

Gemma 4 31Bwon 2 · lost 4

Dolphin 2.5 Mixtral 8x7bwon 2 · lost 4

Gemini 1.5 Prowon 2 · lost 4

Mercury 2won 2 · lost 4

Gemini 2.5 Prowon 2 · lost 4

DeepSeek V4 Prowon 2 · lost 4

Gemma 4 26B A4Bwon 2 · lost 4

LongWriter Glm4 9Bwon 2 · lost 4

Gemini 1.5 Flashwon 2 · lost 4

Qwen 2.5 Instruct (7B)won 2 · lost 4

Qwen3 VL 235B A22B Instructwon 2 · lost 4

GPT-5.6 Astrawon 2 · lost 4

GPT OSS Safeguard 20Bwon 2 · lost 4

Gemini 3.8 Flashwon 2 · lost 4

GPT-6 Solwon 2 · lost 4

GPT-5.6 Solwon 2 · lost 4

Qwen3.5 122B A10Bwon 2 · lost 4

Qwen3 235B A22B Instructwon 2 · lost 4

GPT-5.5won 2 · lost 4

GPT-5.6 Terrawon 2 · lost 4

Claude Opus 4.6won 1 · lost 3

Claude Sonnet 4.6won 1 · lost 3

GLM-5.3 Flashwon 1 · lost 4

Qwen3.5 27Bwon 1 · lost 4

GPT-6 Lunawon 1 · lost 4

SeaLLMs V3 7B Chatwon 1 · lost 5

Qwen2.5 1.5B Instructwon 1 · lost 5

WizardLM 2.8x22Bwon 1 · lost 5

Granite 3.1 2B Instructwon 1 · lost 5

Llama 3.2 3B Instructwon 1 · lost 5

IBM Granite 4.0 Microwon 1 · lost 5

Hunyuan A13B Instructwon 1 · lost 5

Granite 3.2 2B Instructwon 1 · lost 5

Granite 3.0 3B A800M Instructwon 1 · lost 5

Gemma 3 4B ITwon 1 · lost 5

Llama 3.1 8B Instructwon 1 · lost 5

Granite 3.0 2B Instructwon 1 · lost 5

Gemma2 9B Cpt Sea Lionv3 Instructwon 1 · lost 5

Llama 3.1 405B Instructwon 1 · lost 5

Reflection Llama 3.1 70Bwon 1 · lost 5

Apertus 8B Instructwon 1 · lost 5

Llama 3.2 1B Instructwon 1 · lost 5

Qwen2.5 32B Instructwon 1 · lost 5

Qwen2.5 14B Instruct 1Mwon 1 · lost 5

Qwen2 VL 72Bwon 1 · lost 5

GLM-5 Turbowon 1 · lost 5

Granite 3.1 3B A800M Instructwon 1 · lost 5

Phi-3 Medium 4K Instructwon 1 · lost 5

Sarvam 30Bwon 1 · lost 5

Granite 3.1 8B Instructwon 1 · lost 5

Claude 3 Haikuwon 1 · lost 5

Qwen2.5 14B Instructwon 1 · lost 5

Gemini 2.0 Flashwon 1 · lost 5

Phi 3 Medium 128k Instructwon 1 · lost 5

Gemma 3 27B ITwon 1 · lost 5

Qwen2 57B A14B Instructwon 1 · lost 5

Smaug Llama 3 70B Instructwon 1 · lost 5

Phi 3 Small 128k Instructwon 1 · lost 5

Granite 3.0 8B Instructwon 1 · lost 5

MiMo V2.6 Prowon 1 · lost 5

Llama 3 8B Instructwon 1 · lost 5

Kimi K2 Thinkingwon 1 · lost 5

EAI Llama 3.1 8B Instruct SageAlignwon 1 · lost 5

Gemma 3 12B ITwon 1 · lost 5

SeaLLM 7B V2won 1 · lost 5

Apertus 70B Instructwon 1 · lost 5

Llama 4 Maverick Instructwon 1 · lost 5

Granite 4.0 H Microwon 1 · lost 5

Granite 4.0 H Tinywon 1 · lost 5

Phi-3 Small 8K Instructwon 1 · lost 5

Llama 3 70B Instructwon 1 · lost 5

Phi-3 Mini 128K Instructwon 1 · lost 5

Phi 3.5 Mini Instructwon 1 · lost 5

K2 Chatwon 1 · lost 5

Llama 3.1 Tulu 3 8B SFTwon 1 · lost 5

GPT-4.1 nanowon 1 · lost 5

Phi-3 Mini 4K Instructwon 1 · lost 5

Amazon Nova Prowon 1 · lost 5

GPT-4o miniwon 1 · lost 5

Llama 3.1 Tulu 3 8B DPOwon 1 · lost 5

Krutrim 2 Instructwon 1 · lost 5

Qwen3.8 Maxwon 1 · lost 5

Llama 3.1 Tulu 3 8Bwon 1 · lost 5

EAI SageAlign 8B LoRAwon 1 · lost 5

GLM-5.1won 1 · lost 5

Qwen3.5 35B A3Bwon 1 · lost 5

GPT-4.1 miniwon 1 · lost 5

Qwen Maxwon 1 · lost 5

GPT-4won 1 · lost 5

O4 Miniwon 1 · lost 5

Phi 3.5 MoE Instructwon 1 · lost 5

Amazon Nova Microwon 1 · lost 5

GPT-5.6 Lunawon 1 · lost 5

Amazon Nova Litewon 1 · lost 5

Aya Expanse 32Bwon 1 · lost 5

Aya Expanse 8Bwon 1 · lost 5

Llama 3.2 Vision (11B)won 1 · lost 5

Titan Text Express V1won 1 · lost 5

Llama 3.1 Nemotron 70B Instructwon 1 · lost 5

Internlm2 Chat 20Bwon 1 · lost 5

Llama 2 13B Chatwon 1 · lost 5

Llama 2 70B Chatwon 1 · lost 5

Llama 3 8B Instruct RRwon 1 · lost 5

Nova Premierwon 1 · lost 5

Fugu Ultra V2won 1 · lost 5

Granite 4.0 H Smallwon 1 · lost 5

Llama 2 7B Chatwon 1 · lost 5

Grok 4.5won 1 · lost 5

Sarvam 105Bwon 1 · lost 5

Claude 3.7 Sonnetwon 1 · lost 5

GPT-4owon 1 · lost 5

GPT-5.4won 1 · lost 5

O3 Miniwon 1 · lost 5

Qwen2 72B Instructwon 1 · lost 5

Claude Haiku 4.5won 1 · lost 5

Llama 3 8B Instruct MopeyMulewon 1 · lost 5

Claude 3 Sonnetwon 1 · lost 5

GPT-4.1won 1 · lost 5

Cogito 671B V2 P1won 1 · lost 5

Claude Opus 4won 1 · lost 5

Claude Opus 4.7won 1 · lost 5

Qwen2.5 72B Instructwon 1 · lost 5

Claude Sonnet 4.5won 1 · lost 5

Foundation Sec 8B Instructwon 1 · lost 5

Gemma 2 27B ITwon 1 · lost 5

O1 Miniwon 1 · lost 5

Claude Sonnet 4won 1 · lost 5

Meta SecAlign 8Bwon 1 · lost 5

Apriel 1.5 15B Thinkerwon 1 · lost 5

GPT-4 Turbowon 1 · lost 5

GPT-5.1won 1 · lost 5

GPT-5.2won 1 · lost 5

O3won 1 · lost 5

O1won 1 · lost 5

Phi 4won 1 · lost 5

GPT-5 miniwon 1 · lost 5

GPT-5won 1 · lost 5

GPT-5 nanowon 1 · lost 5

Claude 3 Opuswon 1 · lost 5

Inklingwon 1 · lost 5

Hy3won 1 · lost 5

Claude 3.5 Sonnetwon 1 · lost 5

Llama 3.2 Vision (90B)won 0 · lost 6

Qwen3.5 397B A17Bwon 0 · lost 6

Mistral NeMo Minitron 8B Instructwon 0 · lost 6

Claude Opus 5won 0 · lost 6

Grok 4.6won 0 · lost 6

MiniMax M2won 0 · lost 6

MiniMax M2.7won 0 · lost 6

Claude 3.5 Haikuwon 0 · lost 6

Claude Opus 5.5won 0 · lost 6

Muse Spark 1.1won 0 · lost 6

Claude Opus 4.8won 0 · lost 6

Grok 4.7won 0 · lost 6

Claude Sonnet 5won 0 · lost 6

§ 3 · Sources

Where the numbers come from

1 publication, 6 figures. Every one links to the page it was read from.

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

Enkrypt · Jailbreak risk 14%Enkrypt · Harmful content risk 60.6%Enkrypt · CBRN risk 11.5%Enkrypt · Toxicity risk 7.1%Enkrypt · Bias risk 52.5%Enkrypt · Insecure code risk 70.7%

Badge

[![PublicAI Index](https://publicai.io/model-index/badge?model=sarvam-1)](https://publicai.io/model-index/m/sarvam-1)