BenchLeader

Gemini 3 Flash vs GPT-6 Sol

Verdict
  • GPT-6 Sol (max) leads on quality: 67.7 vs 59.8.
  • Gemini 3 Flash (thinking) is stronger in agents & tools, instruction following.
  • GPT-6 Sol (max) is stronger in composite, knowledge, long context, multimodal, reasoning.
  • Gemini 3 Flash (thinking) is 3.6× cheaper ($1.13 vs $4.00 per 1M blended).
  • Gemini 3 Flash (thinking) streams 1.7× faster (218 vs 126 tokens per second).
MetricGemini 3 Flash (thinking)GPT-6 Sol (max)
BenchLeader Index59.867.7
Agents & tools score55.1
Composite score60.786.2
Instruction following score75.6
Knowledge score67.675.4
Long context score64.867.7
Multimodal score63.767.1
Reasoning score56.895.0
Blended price $/M$1.13$4.00
Output speed218 tok/s126 tok/s
Time to first answer6.3 s107.2 s
Context window1.0M1.1M
AA Intelligence Index26.347.5
IFBench78.0%
AA-LCR78.0%83.7%
MMMU-Pro79.9%83.3%
AA-Omniscience10.127.1
Terminal-Bench Hard38.6%
GPQA Diamond (AA)89.8%
Humanity's Last Exam (AA)36.6%47.9%
SciCode (AA)57.6%
τ²-Bench Telecom (AA)80.4%
CritPt8.6%30.9%
GDPval (AA)49.4%
τ²-Bench Banking (AA)20.8%
APEX-Agents (AA)27.7%
Terminal-Bench 4.0 (AA)43.9%
AutomationBench61.6%
GDP.pdf24.8%
MLCR16.1%
AA-Omniscience: accuracy53.4%54.5%
AA-Omniscience: non-hallucination7.0%39.9%
AA-Briefcase1483

Data as of 2026-09-23. Best configuration of each model; every score links to its source on the model pages.

Gemini 3 Flash vs GPT-6 Sol: questions

Is Gemini 3 Flash better than GPT-6 Sol?
GPT-6 Sol (max) leads on quality: 67.7 vs 59.8. The BenchLeader Index combines every independent quality benchmark; GPT-6 Sol (max) is ahead overall as of 2026-09-23, but check the category scores for your use.
Which is cheaper, Gemini 3 Flash or GPT-6 Sol?
Gemini 3 Flash is cheaper: $1.13 against $4.00 per million tokens, blended at three input tokens per output token.
Which is faster, Gemini 3 Flash or GPT-6 Sol?
Gemini 3 Flash streams faster: 218 against 126 output tokens per second.
Which has the larger context window?
GPT-6 Sol accepts more context: 1.1M against 1.0M tokens.