BenchLeader

Claude Opus 5.5 vs Qwen3.8 Max

Verdict
  • Claude Opus 5.5 (max) leads on quality: 72.0 vs 64.2.
  • Claude Opus 5.5 (max) is stronger in agents & tools, coding, composite, knowledge, long context, maths, multimodal, reasoning.
  • Qwen3.8 Max (max) is stronger in human preference.
  • Qwen3.8 Max (max) is 2.7× cheaper ($3.00 vs $8.00 per 1M blended).
  • Claude Opus 5.5 (max) streams 2.6× faster (96 vs 37 tokens per second).
MetricClaude Opus 5.5 (max)Qwen3.8 Max (max)
BenchLeader Index72.064.2
Agents & tools score69.058.2
Coding score82.964.6
Composite score84.770.7
Knowledge score79.262.7
Long context score67.665.4
Maths score74.965.1
Multimodal score71.166.2
Reasoning score76.072.2
Human preference score–68.0
Blended price $/M$8.00$3.00
Output speed96 tok/s37 tok/s
Time to first answer662.1 s58.9 s
Context window1M1M
GPQA Diamond90.6%–
FrontierMath Tiers 1–391.2%–
FrontierMath Tier 495.0%–
OTIS Mock AIME100.0%–
SimpleQA Verified72.2%–
Terminal-Bench64.8%27.0%
SciCode66.9%53.2%
APEX-Agents73.5%63.3%
ProofBench100.0%58.0%
Epoch Capabilities Index–156.4
LMArena Text–1483
LMArena Hard Prompts–1504
LMArena Coding–1524
LMArena WebDev18131672
LMArena Vision–1314
LMArena Agent–2.3
LiveBench83.2%78.5%
LiveBench Reasoning92.2%88.2%
LiveBench Coding89.3%72.9%
LiveBench Agentic Coding71.7%64.7%
LiveBench Mathematics97.1%91.3%
LiveBench Data Analysis80.3%78.4%
LiveBench Language86.3%79.7%
LiveBench Instruction Following65.7%74.1%
AA Intelligence Index v4.3.257.645.4
AA-LCR84.7%80.3%
MMMU-Pro87.7%82.8%
AA-Omniscience46.412.0
GPQA Diamond (AA)–92.8%
Humanity's Last Exam (AA)61.4%43.1%
SciCode (AA)66.9%53.2%
LiveCodeBench–87.8%
MMLU-Pro–88.6%
IOI–68.9%
LegalBench–83.6%
CorpFin–65.8%
TaxEval–75.5%
Terminal-Bench 2.1 (Vals)–67.4%
SWE-bench (Vals)–85.6%
GPQA Diamond (Vals)–93.7%
Vals Index–48.3
ARC-AGI-197.5%–
ARC-AGI-291.7%–
CritPt31.7%20.0%
GDPval-AA v2.168.3%58.6%
τ³-Banking (AA)–51.3%
ITBench SRE (AA)38.2%40.3%
Analyst Agent (AA)56.3%45.0%
APEX-Agents (AA)–42.4%
Code Migration–24.0%
CUA-bench14.0%–
CyberBench–28.6%
Excel Modeling Benchmark–60.1%
Finance Agent v2–50.6%
Harvey's Legal Agent Benchmark–10.4%
Legal Research Bench–47.6%
MedCode–40.7%
MedScribe–85.0%
MMMU-Pro (Vals)–88.0%
MortgageTax–64.0%
MysteryMechanism–23.9%
ProgramBench–0.0%
Public Benefits Bench–67.1%
SAGE–51.3%
SkillsBench–42.0%
Tax Agent Bench–66.0%
Terminal-Bench 4.0 (Vals)–34.3%
Terminal-Bench Science–1.4%
Vals Multimodal Index–65.4%
Vibe Code Bench 1-100–12.8%
Vibe Code Bench v1.1–64.7%
LMArena Maths–1497
LMArena Creative Writing–1470
LMArena Instruction Following–1474
LMArena Multi-turn–1492
LMArena Longer Queries–1492
EBR-bench71.4%–
Mystery Game Puzzles71.0%–
MirrorCode77.4%–
LMCA68.2%–
DTBench98.9%–
CursorBench57.8%–
GDP.pdf30.6%–
FrontierSWE62.3%–
Terminal-Bench 4.0 (AA)59.6%38.9%
Terminal-Bench 2.1 (AA)–88.8%
AutomationBench69.5%56.2%
GDP.pdf26.2%22.8%
MLCR66.7%20.0%
Harvey LAB4.2%–
EnterpriseOps-Gym–47.6%
AA-Omniscience: accuracy66.2%31.9%
AA-Omniscience: non-hallucination41.4%71.2%
AA-Briefcase v1.118071617

Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.

Claude Opus 5.5 vs Qwen3.8 Max: questions

Is Claude Opus 5.5 better than Qwen3.8 Max?
Claude Opus 5.5 (max) leads on quality: 72.0 vs 64.2. The BenchLeader Index combines every independent quality benchmark; Claude Opus 5.5 (max) is ahead overall as of 2026-10-11, but check the category scores for your use.
Is Claude Opus 5.5 better than Qwen3.8 Max for coding?
Claude Opus 5.5 scores higher in coding (83 vs 65 on the category index, where 50 is average).
Is Claude Opus 5.5 better than Qwen3.8 Max for agentic tasks?
Claude Opus 5.5 scores higher in agentic tasks (69 vs 58 on the category index, where 50 is average).
Which is cheaper, Claude Opus 5.5 or Qwen3.8 Max?
Qwen3.8 Max is cheaper: $3.00 against $8.00 per million tokens, blended at three input tokens per output token.
Which is faster, Claude Opus 5.5 or Qwen3.8 Max?
Claude Opus 5.5 streams faster: 96 against 37 output tokens per second.
Which has the larger context window?
Both accept 1M tokens of context.