The LLM benchmark aggregator.

Gemini Exp 1206

Google

Strongest in Agentic coding (#86 of 169, on 1 of its 5 boards), weakest in Reasoning (#142 of 189). Above par in 0 of 4 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and Claude Opus 5 and ahead of GPT-5.2 Codex 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.

Coding48.7−17.7#90/1761/6

Agentic coding48.5−18.5#86/1691/5

Reasoning44.6−20.2#142/1891/5

Reasoning41.3−25.4#114/1431/3

§ 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 Gemini Exp 1206, left for the other.

Mercury 2.5won 3 · lost 0

Command Awon 3 · lost 0

Mistral Medium 3.5won 3 · lost 0

Laguna XS.2won 3 · lost 0

Laguna M.1won 3 · lost 0

Qwen3.6 27Bwon 3 · lost 0

GPT-4 Turbowon 3 · lost 0

Grok Build 0.1won 3 · lost 0

Claude 3.5 Haikuwon 3 · lost 0

NVIDIA Nemotron 3.5 Lightning 30B A3Bwon 4 · lost 0

GPT-4o Miniwon 4 · lost 0

Claude Haiku 4.5won 4 · lost 0

Mistral Large 3won 4 · lost 0

GPT-4owon 4 · lost 0

Gemma 4 31Bwon 4 · lost 0

Llama 4 Maverick Instructwon 4 · lost 0

Gemini 2.0 Flash Thinkingwon 4 · lost 0

Gemini 2.0 Flashwon 4 · lost 0

O1 Miniwon 4 · lost 0

Muse Spark Openwon 4 · lost 0

GPT OSS 120Bwon 3 · lost 1

GPT-4.1 Nanowon 3 · lost 1

Gemini 3.5 Flash Litewon 3 · lost 1

MiniMax M3won 3 · lost 1

DeepSeek V3won 3 · lost 1

GPT-4.1 Miniwon 3 · lost 1

Grok 4.3won 2 · lost 1

Gemini 3.1 Flash Litewon 2 · lost 1

Ling 3.0 Flashwon 2 · lost 1

GLM-4.6won 2 · lost 1

Qwen3 Maxwon 2 · lost 1

Qwen3.6 Pluswon 2 · lost 1

MiniMax M2.7won 2 · lost 1

Qwen 3.5 Pluswon 2 · lost 1

Nemotron 3 Nano 4Bwon 2 · lost 1

Gemma 4 E4Bwon 2 · lost 1

G9v3 3Bwon 2 · lost 1

Mimo V2.5won 2 · lost 1

K2 Horizon 7Bwon 2 · lost 1

Qwen3.5 Flashwon 2 · lost 1

Mimo V2.5 Prowon 2 · lost 1

Granite 4.2 3Bwon 2 · lost 1

Kimi K2.6won 2 · lost 1

GPT-5.2 Codexwon 2 · lost 1

NVIDIA Nemotron 3 Ultra 550B A55Bwon 2 · lost 2

Grok 4.1 Fastwon 2 · lost 2

Grok 4 Fastwon 2 · lost 2

Grok 4.20won 2 · lost 2

Kimi K2.5won 2 · lost 2

GPT-5 Miniwon 2 · lost 2

Gemini 3 Flashwon 2 · lost 2

Inklingwon 2 · lost 2

GPT-5.4 Nanowon 2 · lost 2

Claude Opus 4.5won 2 · lost 2

Qwen3.7 Maxwon 2 · lost 2

GPT-5.4 Miniwon 2 · lost 2

Gemini 3.1 Prowon 2 · lost 2

Kimi K2 Thinkingwon 2 · lost 2

Claude Sonnet 4.5won 2 · lost 2

MiniMax M2.5won 2 · lost 2

GPT-5.1won 2 · lost 2

Inkling Smallwon 2 · lost 2

Nemotron 3.5 Super VLwon 2 · lost 2

GLM-5won 2 · lost 2

Gemini 3 Prowon 2 · lost 2

Claude 3.5 Sonnetwon 2 · lost 2

DeepSeek V4 Flash Visionwon 2 · lost 2

GLM-5.1won 2 · lost 2

DeepSeek V3.2won 2 · lost 2

Kimi K2.7 Codewon 2 · lost 2

Claude Sonnet 4.6won 2 · lost 2

GLM-4.7won 2 · lost 2

GPT-4.5won 2 · lost 2

GPT-4.1won 2 · lost 2

Qwen3.5 4Bwon 1 · lost 2

Gemma 4 12Bwon 1 · lost 2

Granite 4.2 30Bwon 1 · lost 2

Qwen3 235B A22B Instructwon 1 · lost 2

Gemini 2.5 Prowon 1 · lost 3

Ox Alphawon 1 · lost 3

Grok 3won 1 · lost 3

Kimi K2won 1 · lost 3

O3 Miniwon 1 · lost 3

Granite 4.2 8Bwon 0 · lost 3

K2 Horizon 32Bwon 0 · lost 3

Qwen3.5 9Bwon 0 · lost 3

G9v3 39A5Bwon 0 · lost 3

K2 Horizon 3.7Bwon 0 · lost 3

NVIDIA Nemotron 3 Super 120B A12Bwon 0 · lost 3

Qwen3.6 35B A3Bwon 0 · lost 3

DeepSeek V4won 0 · lost 3

K2 Horizon MoVA 36B A4Bwon 0 · lost 3

Muse Sparkwon 0 · lost 3

Muse Glimmer-30Bwon 0 · lost 3

K2 Horizon 375B A23Bwon 0 · lost 3

Ember 1won 0 · lost 3

Qwen3.8 Flash Nextwon 0 · lost 3

Muse Spark 1.1won 0 · lost 3

Mimo V2.6 Flashwon 0 · lost 3

Hy4won 0 · lost 3

Muse Wonder Fullwon 0 · lost 3

Gemini 3.5 Flashwon 0 · lost 4

Qwen3.6 Maxwon 0 · lost 4

Gemini 3.6 Flashwon 0 · lost 4

GPT-5.2won 0 · lost 4

MiniMax M2.1won 0 · lost 4

Claude Opus 4.6won 0 · lost 4

Mistral Large 4won 0 · lost 4

Grok 4won 0 · lost 4

GLM-5.3 Flashwon 0 · lost 4

GPT-5won 0 · lost 4

Beam 1.0won 0 · lost 4

Qwen3.8 Maxwon 0 · lost 4

Gemini 3.7 Flashwon 0 · lost 4

Claude Sonnet 4won 0 · lost 4

Qwen3.8 Flashwon 0 · lost 4

Gemini 2.5 Flashwon 0 · lost 4

Grok 3 Miniwon 0 · lost 4

GPT-6 Lunawon 0 · lost 4

GPT-5.4won 0 · lost 4

Gemini 3.8 Flashwon 0 · lost 4

GPT-5.6 Lunawon 0 · lost 4

Kimi K3won 0 · lost 4

GLM-5.2won 0 · lost 4

O1won 0 · lost 4

Claude Sonnet 5won 0 · lost 4

Qwen3.8 27Bwon 0 · lost 4

DeepSeek V4 Flashwon 0 · lost 4

Claude 3.7 Sonnetwon 0 · lost 4

Claude Opus 4.7won 0 · lost 4

Claude Opus 4won 0 · lost 4

Step 5won 0 · lost 4

Claude Opus 4.8won 0 · lost 4

Grok 4.5won 0 · lost 4

Muse Spark 1.2won 0 · lost 4

GPT-5.5won 0 · lost 4

Grok 4.7won 0 · lost 4

Mimo V2.6 Prowon 0 · lost 4

Claude Haiku 5.5won 0 · lost 4

GPT-5.6 Terrawon 0 · lost 4

Grok 4.6won 0 · lost 4

Muse Spark 1.3won 0 · lost 4

DeepSeek R1won 0 · lost 4

O3 Prowon 0 · lost 4

DeepSeek V4 Prowon 0 · lost 4

GLM-5.3won 0 · lost 4

Claude Sonnet 5.5won 0 · lost 4

GPT-6 Solwon 0 · lost 4

O4 Miniwon 0 · lost 4

GPT-5.6 Solwon 0 · lost 4

O3won 0 · lost 4

Muse Wonderwon 0 · lost 4

GPT-6.1 Solwon 0 · lost 4

Gemini 4 Argonwon 0 · lost 4

GPT-6 Astrawon 0 · lost 4

DeepSeek V4.1 Flashwon 0 · lost 4

Claude Fable 5won 0 · lost 4

Claude Fable 5.1won 0 · lost 4

Claude Opus 5won 0 · lost 4

Claude Opus 5.5won 0 · lost 4

§ 3 · Sources

Where the numbers come from

2 publications, 2 figures. Every one links to the page it was read from.

Aider polyglot ↗1 measureread 2026-10-19

Aider polyglot 38.2%

SimpleBench ↗1 measureread 2026-10-19

SimpleBench 31.1%

Badge

[![PublicAI Index](https://publicai.io/model-index/badge?model=gemini-exp-1206)](https://publicai.io/model-index/m/gemini-exp-1206)