BenchLeader

GPT-5.6 Sol vs Qwen3.8 Max (0902)

Verdict
  • GPT-5.6 Sol (high) leads on quality: 66.0 vs 57.1.
  • GPT-5.6 Sol (high) is stronger in agents & tools, coding, composite, instruction following, knowledge, long context, multimodal.
  • Qwen3.8 Max (0902) (xhigh) is stronger in reasoning, maths.
  • Qwen3.8 Max (0902) (xhigh) is 2.7× cheaper ($3.00 vs $8.00 per 1M blended).
  • GPT-5.6 Sol (high) streams 1.6× faster (61 vs 38 tokens per second).
MetricGPT-5.6 Sol (high)Qwen3.8 Max (0902) (xhigh)
BenchLeader Index66.057.1
Agents & tools score82.5
Coding score72.4
Composite score75.7
Instruction following score64.7
Knowledge score70.455.9
Long context score65.1
Multimodal score65.5
Reasoning score63.366.9
Maths score61.2
Blended price $/M$8.00$3.00
Output speed61 tok/s38 tok/s
Time to first answer12.6 s2.0 s
Context window1.1M1M
GPQA Diamond92.3%
FrontierMath Tiers 1–365.6%
FrontierMath Tier 434.1%
OTIS Mock AIME100.0%
SimpleQA Verified47.3%
SciCode56.9%
WeirdML88.8%
AA Intelligence Index42.5
IFBench69.2%
AA-LCR81.7%
MMMU-Pro81.8%
AA-Omniscience20.4
Terminal-Bench Hard62.1%
GPQA Diamond (AA)92.8%
Humanity's Last Exam (AA)46.0%
SciCode (AA)57.8%
τ²-Bench Telecom (AA)83.3%
EnigmaEval37.1%
ARC-AGI-197.0%
ARC-AGI-285.4%
ARC-AGI-32.2%

Data as of 2026-09-13. Best configuration of each model; every score links to its source on the model pages.

GPT-5.6 Sol vs Qwen3.8 Max (0902): questions

Is GPT-5.6 Sol better than Qwen3.8 Max (0902)?
GPT-5.6 Sol (high) leads on quality: 66.0 vs 57.1. The BenchLeader Index combines every independent quality benchmark; GPT-5.6 Sol (high) is ahead overall as of 2026-09-13, but check the category scores for your use.
Which is cheaper, GPT-5.6 Sol or Qwen3.8 Max (0902)?
Qwen3.8 Max (0902) is cheaper: $3.00 against $8.00 per million tokens, blended at three input tokens per output token.
Which is faster, GPT-5.6 Sol or Qwen3.8 Max (0902)?
GPT-5.6 Sol streams faster: 61 against 38 output tokens per second.
Which has the larger context window?
GPT-5.6 Sol accepts more context: 1.1M against 1M tokens.