The LLM benchmark aggregator.

Gemini 2.0 Flash Thinking

Google

Strongest in Professional (#93 of 194, on 1 of its 2 boards), weakest in Reasoning (#147 of 195). Above par in 2 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and Claude Opus 5 and ahead of Claude 3.5 Haiku and Qwen3.6 Plus.

§ 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.

Professional50.2−12.2#93/1941/2

Finance50.5−11.9#96/1621/1

Coding44.5−21.6#130/1791/6

Agentic coding44−22.7#127/1731/5

Reasoning44.2−21.2#147/1951/5

Reasoning40.8−28.2#119/1471/3

§ 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 2.0 Flash Thinking, left for the other.

Llama 3.3 70B Instructwon 4 · lost 0

Grok 2won 4 · lost 0

Gemini 1.5 Prowon 4 · lost 0

Llama 3.1 405B Instructwon 4 · lost 0

NVIDIA Nemotron 3.5 Lightning 30B A3Bwon 5 · lost 0

Mercury 2.5won 5 · lost 0

Mistral Medium 3.5won 5 · lost 0

Laguna XS.2won 5 · lost 0

Nemotron 3.5 Super VLwon 5 · lost 0

Command Awon 5 · lost 0

GPT-4owon 5 · lost 0

Laguna M.1won 5 · lost 0

Smaug Nemotron 3.5won 5 · lost 0

GPT-4o miniwon 6 · lost 0

Llama 4 Maverick Instructwon 6 · lost 0

Gemma 4 31Bwon 5 · lost 1

Mistral Large 3won 5 · lost 1

GPT-4.1 nanowon 5 · lost 1

Grok 4.3won 4 · lost 1

Gemini 3.1 Flash-Litewon 4 · lost 1

Ling 3.0 Flashwon 4 · lost 1

MiniMax M2.7won 4 · lost 1

Llama 4 Scout Instructwon 3 · lost 1

Ling 3.0 Flash Finwon 3 · lost 1

GPT-4 Turbowon 3 · lost 1

Grok 4.1 Fastwon 4 · lost 2

Grok 4.20won 4 · lost 2

Claude Haiku 4.5won 4 · lost 2

GPT OSS 120Bwon 4 · lost 2

GPT-5.4 nanowon 4 · lost 2

Gemini 3.5 Flash-Litewon 4 · lost 2

Gemini 2.0 Flashwon 4 · lost 2

DeepSeek V3won 4 · lost 2

Qwen3.6 27Bwon 3 · lost 2

GLM-4.6won 3 · lost 2

Qwen3 Maxwon 3 · lost 2

Qwen3.6 Pluswon 3 · lost 2

Claude 3.5 Haikuwon 3 · lost 2

DeepSeek V3.1won 2 · lost 2

GPT-5 nanowon 2 · lost 2

Qwen3.7 Pluswon 2 · lost 2

Gemini 2.0 Prowon 2 · lost 2

GPT-4.5won 2 · lost 2

NVIDIA Nemotron 3 Ultra 550B A55Bwon 3 · lost 3

Grok 4 Fastwon 3 · lost 3

Kimi K2.5won 3 · lost 3

Inklingwon 3 · lost 3

Claude 3.5 Sonnetwon 3 · lost 3

Kimi K2won 3 · lost 3

O3 Miniwon 3 · lost 3

MiMo V2.5won 2 · lost 3

O1 Miniwon 2 · lost 3

Beam 1.0won 2 · lost 3

GPT-5 miniwon 2 · lost 4

Gemini 3 Flashwon 2 · lost 4

Claude Opus 4.5won 2 · lost 4

MiniMax M2.5won 2 · lost 4

Muse Spark Openwon 2 · lost 4

DeepSeek V3.2won 2 · lost 4

GLM-4.7won 2 · lost 4

MiniMax M2.1won 2 · lost 4

GPT-4.1won 2 · lost 4

Claude Sonnet 4won 2 · lost 4

DeepSeek R1won 2 · lost 4

Claude Opus 4.1won 1 · lost 3

Ox Alphawon 1 · lost 3

Qwen3.5 Flashwon 1 · lost 4

MiMo V2.5 Prowon 1 · lost 4

DeepSeek V4won 1 · lost 4

MiniMax M3.1 Flashwon 1 · lost 4

GPT-6.1 Terrawon 1 · lost 4

Qwen3.7 Maxwon 1 · lost 5

GPT-5.4 miniwon 1 · lost 5

MiniMax M3won 1 · lost 5

Inkling Smallwon 1 · lost 5

GPT-4.1 miniwon 1 · lost 5

GLM-5.1won 1 · lost 5

Qwen3.6 Maxwon 1 · lost 5

GLM-5.3 Flashwon 1 · lost 5

Grok 4won 1 · lost 5

GPT-6 Lunawon 1 · lost 5

Grok 3won 1 · lost 5

Step 5won 1 · lost 5

Qwen3 235B A22B Instructwon 1 · lost 5

O4 Miniwon 1 · lost 5

Kimi K2.7 Codewon 0 · lost 4

Gemini Exp 1206won 0 · lost 4

O3 Prowon 0 · lost 4

Qwen 3.5 Pluswon 0 · lost 5

Muse Sparkwon 0 · lost 5

Kimi K2.6won 0 · lost 5

Kimi K3.1 Prowon 0 · lost 5

Ember 1won 0 · lost 5

Muse Spark 1.1won 0 · lost 5

Inkling 2 Smallwon 0 · lost 5

MiMo V2.6 Flashwon 0 · lost 5

Muse Emberwon 0 · lost 5

Hy4won 0 · lost 5

Claude Fable 5.2won 0 · lost 5

Gemini 4 Carbonwon 0 · lost 5

Muse Wonder Fullwon 0 · lost 5

Kimi K2 Thinkingwon 0 · lost 6

Gemini 3.1 Prowon 0 · lost 6

Claude Sonnet 4.5won 0 · lost 6

GPT-5.1won 0 · lost 6

GLM-5won 0 · lost 6

Gemini 3 Prowon 0 · lost 6

Gemini 2.5 Prowon 0 · lost 6

Gemini 3.5 Flashwon 0 · lost 6

Claude Sonnet 4.6won 0 · lost 6

Gemini 3.6 Flashwon 0 · lost 6

GPT-5.2won 0 · lost 6

Claude Opus 4.6won 0 · lost 6

GPT-5won 0 · lost 6

Qwen3.8 27Bwon 0 · lost 6

Gemini 3.7 Flashwon 0 · lost 6

Gemini 3.8 Flashwon 0 · lost 6

GPT-5.4won 0 · lost 6

Gemini 2.5 Flashwon 0 · lost 6

Grok 3 Miniwon 0 · lost 6

Kimi K3won 0 · lost 6

Qwen3.8 Maxwon 0 · lost 6

Grok 4.5won 0 · lost 6

GLM-5.2won 0 · lost 6

MiMo V2.6 Prowon 0 · lost 6

O1won 0 · lost 6

DeepSeek V4 Flashwon 0 · lost 6

Claude Opus 4.7won 0 · lost 6

GPT-5.6 Lunawon 0 · lost 6

Claude 3.7 Sonnetwon 0 · lost 6

Claude Opus 4won 0 · lost 6

Claude Sonnet 5won 0 · lost 6

Mistral Large 4won 0 · lost 6

Grok 4.7won 0 · lost 6

GPT-5.5won 0 · lost 6

Claude Opus 4.8won 0 · lost 6

Claude Haiku 5.5won 0 · lost 6

Muse Spark 1.2won 0 · lost 6

Grok 4.6won 0 · lost 6

Claude Sonnet 5.5won 0 · lost 6

GPT-5.6 Terrawon 0 · lost 6

Muse Spark 1.3won 0 · lost 6

GPT-6 Solwon 0 · lost 6

DeepSeek V4 Prowon 0 · lost 6

GLM-5.3won 0 · lost 6

GPT-5.6 Solwon 0 · lost 6

Muse Wonderwon 0 · lost 6

O3won 0 · lost 6

GPT-6.1 Solwon 0 · lost 6

DeepSeek V4.1 Flashwon 0 · lost 6

Claude Fable 5won 0 · lost 6

Gemini 4 Argonwon 0 · lost 6

GPT-6 Astrawon 0 · lost 6

Claude Fable 5.1won 0 · lost 6

Claude Opus 5won 0 · lost 6

Claude Opus 5.5won 0 · lost 6

§ 3 · Sources

Where the numbers come from

3 publications, 3 figures. Every one links to the page it was read from.

Aider polyglot ↗1 measureread 2026-11-12

Aider polyglot 18.2%

SimpleBench ↗1 measureread 2026-11-12

SimpleBench 30.7%

Vals.ai ↗1 measureread 2026-11-12

Vals · TaxEval 69.79%

Badge

[![PublicAI Index](https://publicai.io/model-index/badge?model=gemini-2-0-flash-thinking)](https://publicai.io/model-index/m/gemini-2-0-flash-thinking)