BenchLeader

GPT-5.4 Pro vs Qwen3.8-Flash-Next

Verdict
  • GPT-5.4 Pro leads on quality: 64.3 vs 57.7.
  • GPT-5.4 Pro is stronger in instruction following, knowledge, multimodal, reasoning.
  • Qwen3.8-Flash-Next is stronger in agents & tools, coding, composite, long context.
  • Qwen3.8-Flash-Next is 293× cheaper ($0.230 vs $67.50 per 1M blended).
  • Qwen3.8-Flash-Next streams 50.0× faster (50 vs 1 tokens per second).
MetricGPT-5.4 ProQwen3.8-Flash-Next
BenchLeader Index64.357.7
Instruction following score67.3
Knowledge score73.656.0
Multimodal score69.863.1
Reasoning score75.3
Agents & tools score48.0
Coding score71.2
Composite score63.9
Long context score63.9
Blended price $/M$67.50$0.230
Output speed1 tok/s50 tok/s
Time to first answer6.3 s42.8 s
Context window1.1M256k
Humanity's Last Exam44.3%
SimpleBench74.1%
Epoch Capabilities Index158.9
LMArena WebDev1635
LMArena Agent0.4
LiveBench76.2%
LiveBench Reasoning87.4%
LiveBench Coding72.5%
LiveBench Agentic Coding61.6%
LiveBench Mathematics85.8%
LiveBench Data Analysis74.2%
LiveBench Language74.6%
AA Intelligence Index39.9
AA-LCR79.7%
MMMU-Pro79.8%
AA-Omniscience-9.7
GPQA Diamond (AA)92.3%
Humanity's Last Exam (AA)38.0%
SciCode (AA)50.6%
MultiChallenge69.2%
VISTA53.9%
MultiNRC62.3%
TutorBench56.6%

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

GPT-5.4 Pro vs Qwen3.8-Flash-Next: questions

Is GPT-5.4 Pro better than Qwen3.8-Flash-Next?
GPT-5.4 Pro leads on quality: 64.3 vs 57.7. The BenchLeader Index combines every independent quality benchmark; GPT-5.4 Pro is ahead overall as of 2026-09-13, but check the category scores for your use.
Which is cheaper, GPT-5.4 Pro or Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next is cheaper: $0.230 against $67.50 per million tokens, blended at three input tokens per output token.
Which is faster, GPT-5.4 Pro or Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next streams faster: 50 against 1 output tokens per second.
Which has the larger context window?
GPT-5.4 Pro accepts more context: 1.1M against 256k tokens.